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Introduction

Spring framework has been a popular and lightweight application development framework widely used by the developer community. It has gained prominence due to its ability to create high-performing, quickly testable applications and emphasize the reusability of codes. Spring framework is open-source and is primarily a Java platform. 

The Spring framework allows developers to create enterprise Java applications with various extensions and the POJO programming models to make development easier. The rise in popularity of this framework is evident, with 15 out of the top 100 most popular libraries being associated with the Spring framework on GitHub. Furthermore, the increasing demand has led to several job opportunities. 

Therefore, all the aspirants and experienced developers aiming for higher positions on the hierarchical ladder must upskill themselves with Spring framework essentials to achieve some of the industry’s exciting and lucrative career opportunities today.

Releated reading: Top 10 Online Courses to Learn C++ Programming

1. Building Cloud Services with the Java Spring Framework – Coursera

Building Cloud Services with the Java Spring Framework – Coursera

This program is ideal for learning advanced functionalities of the Spring framework. It is offered on Coursera by Vanderbilt University. In this course, the learners will learn Spring framework concepts used for building cloud services with the help of object-oriented programming and design techniques. In addition, the learners will explore concepts like Java servlets and various Java Spring framework features, including cloud computing platforms. 

Besides, the learners will be familiar with concepts like building a secure and scalable cloud platform and achieving scalability efficiently. 

Finally, the learners will delve into Spring security dependency concepts and create robust cloud services using the Spring framework. The course’s prerequisites require learners to have essential Java programming experience. 

The course curriculum includes:

  • HTTP
  • Mime Types and Content-Type Headers
  • Request Body Encoding
  • HTTP Response Codes
  • Cookies
  • Protocol Layering and HTTP Design Methodologies
  • REST and Push Messages
  • Servlets
  • Cloud Service with a Servlet
  • Request Routing and Web
  • Securely Handling Client Data and Avoiding Injection Attacks
  • Building Cloud Services on HTTP
  • Spring Controllers
  • Spring Dispatcher Servlet and Controller Abstraction
  • Accepting Client Data with Path Variable Annotations
  • Spring Boot and Application Structure
  • Horizontal Scaling
  • Load Balancing
  • Spring Dependency Injection
  • Spring Configuration Annotations
  • Object to Database Mapping
  • Spring Repositories
  • Spring Data REST
  • NoSQL Database
  • Spring Data MongoDB
  • Optimizing Query Patterns and Reads and Writes
  • Deploying to Amazon Elastic Beanstalk

Instructor: Dr. Jules White and Dr. Douglas C. Schmidt

Level: Intermediate

Duration: 14 hours

User Review: 4.3/5

No. of Reviews: 205

Price: Free Enrollment (Additional charges for certification may apply)

2. Become a Java Web Developer Nanodegree Program – Udacity

This is a specialization course on Udacity. The training program is focused on providing learners with the advanced skills required for the Java programming language. Additionally, the essential aspects of large-scale enterprise applications, the fundamentals of the Spring framework, the associated integrations and plugins are covered in detail. Moreover, the learners will explore the concepts of web services, APIs, microservices, and RESTFUL web service uses.

There are practical demonstrations that allow learners to learn to develop REST and GraphQL APIs and understand how to test the APIs and web services and the security aspects.  The learners will also cover essential concepts like data stores and building applications that can read and write relational databases with the help of Java persistence API and SQL.

Finally, the concepts on standard design patterns and easy testing of a persistence layer using Spring boot application are covered in-depth. The course’s final module also provides training for critical areas of development, best practices for authorization and authentication, and CI/CD pipeline for deployment is explored with hands-on sessions. 

There are perquisites for the course that includes intermediate knowledge of Java and web development experience for the potential participants of the course.

Instructor: Kesha Williams, Sareeta Panda, Peter Zastoupil, and Alex Pritchard

Level: Intermediate

Duration: 4 months

User Review: 4.4/5

No. of Reviews: 350

Price: $310.8/Per Month and $1056.8 for 4-Month Access

3. Spring Framework Masterclass – Java Spring the Modern Way – Udemy

The online tutorial is offered on Udemy. This program is among the bestselling courses on the platform and is primarily focused on areas like the features of Spring, Spring Boot, and Spring modules. In addition, the learners will learn the uses of JDBC, AOP, and Data JPA through a hands-on approach. The learners will also be introduced to Spring boot, unit testing, Spring JDBC, Tomcat embedded server, and more. The key takeaways from the course include:

  • Basics of Spring Framework
  • Spring Annotations
  • Spring MVC in–depth
  • Spring Boot Starter and Basics of Spring Boot
  • Basics of Eclipse
  • Basic Concepts of Web Application using JSP Servlet and Spring MVC
  • Unit Testing using Junit, Mockito using XML and Java Spring Application Contexts

The course modules are:

  • Introduction to Spring Framework
  • Spring Dependencies
  • Basic tools and Frameworks
  • Unit Testing with Spring Framework
  • Spring Boot in 10 Steps
  • Spring AOP
  • Interacting with Databases
  • Web Applications

Instructor: In28 Minutes Official Team

Level: Beginner

Duration: 12 hours

User Review: 4.4/5

No. of Reviews: 19,869

Price: $47.8

4. Java Spring Tutorial Masterclass- Learn Spring Framework 5 – Udemy

Java Spring Tutorial Masterclass- Learn Spring Framework 5 – Udemy

The course is available on Udemy.  This training program focuses on providing learners with the core components of Java programming and the Spring framework.

Additionally, the learners will deep dive into the concepts of the Java template engine used with the Spring framework.  Besides, the concepts on various tools for building single and multi-module projects are covered with practical lab sessions. 

There are additional modules on Thymeleaf 4 and Maven 3. Finally, the concepts on Spring data, Java persistence layer, hibernate and database versioning are covered in-depth to build a comprehensive Spring developer skill. 

The course curriculum includes:

  • Introduction and Setup
  • New Spring 5
  • Multi-module Spring Project
  • Lombok Introduction
  • Spring MVC
  • Spring Boot 2 Introduction and Thymeleaf 3
  • Gradle Introduction
  • Introduction to Java EE
  • Spring Framework Features
  • Bean Configuration
  • Configuring Spring with Annotations
  • Introduction to MySQL

Instructor: Tim Buchalka and Goran Lochert

Level: Beginner

Duration: 45 hours and 25 minutes

User Review: 4.6/5

No. of Reviews: 5642

Price: $47.8

5. Become a Spring Developer – LinkedIn Learning

Become a Spring Developer – LinkedIn Learning

This is a learning path that comprises various courses ranging from beginner, intermediate and advanced concepts. It is available on LinkedIn Learning

The course offers learners to learn the basics of the Spring framework. Furthermore, the learners will cover the concepts on the framework’s core features for building Java applications for enterprises, uses of Angular and web development. 

In addition, the learners will be familiar with Spring boot to build dynamic and data-driven applications and the importance of REST APIs. Besides, the learners will delve into practical implementations of MVC apps in Spring and learn to test and deploy codes.

Finally, the learners will explore the security requirements for applications and services and the components of full-stack development. 

The learners will deep dive into concepts of developer stack for building applications by pairing with React for front-end requirements and Spring framework for a fully-featured backend. 

The course modules are:

  • Learning Spring with Spring Boot
  • Spring Boot 2:  Essential Training
  • Spring Framework in Depth
  • Creating the First Spring Boot Microservice
  • Extending, Securing, and Dockerizing Spring Boot Microservice
  • Spring MVC
  • Spring Data 2
  • Spring Security
  • Building Full-Stack Apps with React and Spring

Instructor: Frank P Moley III, Mary Ellen Bowman, Ketkee Aryamane, Emmanuel Henri

Level: Beginner/ Intermediate

Duration: 21 hours

User Review: NA

No. of Reviews: NA

Price: 1-Month Free Trial (Prices may be applicable after trial period)

6. Full Stack Java Developer- Java, JSP, Restful, WS, and Spring – Udemy

Full Stack Java Developer- Java, JSP, Restful, WS, and Spring – Udemy

This certification program is available on Udemy. The course covers the essentials of building web applications using the Java programming language. The learners will cover the topics on JSP, RESTFUL, WS, and the Spring framework features. 

Additionally, the learners will explore how to connect to the database and the important tools and functions required for Java developers. Moreover, the learners will understand the enterprise-level web applications development process and cover advanced topics such as multithreading, Lambdas, collections debugging, and introduction to GIT. Next, the learners will gain knowledge about JSP and servlets and the uses of Hibernate. 

The participants need to complete multiple projects in each module with the core technologies covered in the program. Finally, the learners will deep dive into the concepts of Spring framework, RESTFUL web services, and Spring boot essentials. 

The course modules are:

  • Introduction
  • Java: Getting Started
  • Decision Making under Java
  • Flow Control and Methods
  • Object-Oriented Programming Concepts
  • Java Core Concepts
  • Array and Collections Framework
  • Generics and Multi-Threading
  • Lambda Expression
  • File Handling in Java and Debugging
  • JSP and Servlets
  • Java Beans and Session Management
  • JSTL and Building Custom Tag
  • Add/Update/Delete Records into Database
  • Hibernate and Spring 5 Introduction
  • Inversion of Control and Dependency Injection
  • Autowire, Spring Bean, IDE Setup, Spring MVC, Spring Form Elements, and Spring Database Connectivity
  • RESTFUL API and Spring Boot Background
  • Spring Boot MVC and Microservices

Instructor: Study Easy Organization and Chaand Sheikh

Level: Beginner/Intermediate

Duration:64 hours and 48 minutes

User Review: 4.4/5

No. of Reviews: 3746

Price: $47.8

7.  Building Scalable Java Microservices with Spring Boot and Spring Cloud – Coursera

Building Scalable Java Microservices with Spring Boot and Spring Cloud – Coursera

Google offers this certification course on the Coursera platform. The learners will deep dive into building Java applications using the Spring framework and Spring boot concepts on Google cloud in this program. 

In addition, the learners will learn to configure their applications using Spring boot and understand the functionalities of how to send and receive messages with Spring integration. 

There are also additional concepts on Cloud SQL for managing the relational database for the Java applications and being familiar with concepts like migration to Cloud Spanner and learning to trace and debug Spring applications with Google operations suite. The prerequisite includes working knowledge of Java programming language and the associated tools such as Maven and Gradle. 

The course curriculum includes:

  • Introduction to Google Cloud Platform
  • Introduction to Google Cloud Services and Spring Boot
  • Building Demo Application

Instructor: Google Cloud Professionals

Level: Intermediate

Duration: 13 hours

User Review: 4.3/5

No. of Reviews: 903

Price: Free Enrollment (Additional charges for certification may apply)

8. Learn Spring – Codecademy

Learn Spring – Codecademy

This is a beginner-oriented tutorial available on Codecademy. In this program, the learners will learn to build RESTFUL APIs with annotations using Spring and Spring boot.

Moreover, the learners will be familiar with the Spring framework and its features, file structure and understand how to test the application using the browser and the command-line tool. 

In addition, the learners will explore the concepts of Spring beans, the application context, dependency injection, and how Spring and Spring boot are integrated into development. 

Finally, the learners will be able to perform addition, deletion, or upgrade the database’s information using JPA and H2 technologies. There are also hands-on sessions that allow learners to gain mastery of programming skills to build applications, cloud services, front-end web applications, and microservices using the Spring framework. 

The course contents are:

  • How does Spring Work?
  • Spring Controllers
  • Boots and Beans
  • Data Strategies
  • Spring Data and JPA

Instructor: Industry Professional

Level: Beginner

Duration: 6 hours

User Review: NA

No. of Reviews: NA

Price: Prices available on Sign-Up

9. Spring Boot Tutorial for Beginners (Java Framework) – Lead Academy

Spring Boot Tutorial for Beginners (Java Framework) – Lead Academy

This is a comprehensive training program on Spring framework and Spring boot available on Lead Academy. The course is beginner-oriented and focuses on enhancing Java programming skills. The learners will deepen their knowledge about the Spring framework and its integration alongside Spring boot in developing enterprise-level applications. There are practical demonstrations and hands-on sessions, including access to additional training materials.

The learners will also cover the essentials of Spring framework features, including building their first Spring boot application. There is no prerequisite for the course, and it is self-paced with provision for support from industry professionals. The course curriculum includes:

  • Spring Boot Tutorial
  • Certification

Instructor: Industry Professional

Level: Beginner

Duration: Self-Paced

User Review: 4.6/5

No. of Reviews: 502

Price: Prices available on Sign-Up

10. Java Training in Spring – Simplilearn

This is an advanced course on Spring framework and Java programming on Simplilearn. The course is focused on covering various aspects of Java programming and the basic principles of Java, Core Java, J2EE, Java 8, and the JDBC architecture. 

Additionally, the learners will cover the Spring framework, SOA, and JUnit, including advanced concepts on methods, loops, arrays, constructors, and operators. 

At the end of the course, the learners will thoroughly understand concepts and implementations like Java EE, Java servlet, core Java 8 components, Hibernate and Spring framework, SOA and web services, multithreading and exception handling techniques, and J2EE HTTP protocol and HTML. 

The course curriculum includes:

  • Introduction to Java EE
  • Java Servlet I and II
  • Java Server Pages
  • Introduction to Hibernate
  • Hibernate Queries and Relationship
  • Introduction to Spring
  • Spring AOP
  • Spring JDBC and Spring Hibernate
  • Spring MVC
  • SOA and Web Services
  • Core Java (Free Course Module)

Instructor: Industry Professional

Level: Advanced

Duration: Self-Paced

User Review: 4.6/5

No. of Reviews: 917

Price: $349

11. Spring Framework Certification Training – Edureka

Edureka’s Spring framework training program covers all the essential concepts on the Spring framework and the latest trends involving this Java application framework. The course introduces the concepts of dependency injection and offers hands-on sessions to create Spring applications. 

In addition, the learners will understand how to integrate Maven and the importance of AOP and Hibernate integration with Spring. Besides, the learners will also explore concepts like Spring MVC and Apache Tiles, and JSF to create user views. 

Finally, the learners will learn to add security features in Spring applications using Log4j as a logger and test JUnit. The final module allows learners to gain practical exposure to create web applications using the Spring framework. 

The key takeaways of the course include:

  • Spring Framework Architecture
  • Spring’s Dependency Injection and Autowiring feature
  • Build application using Maven
  • Aspect-Oriented Programming (AOP) and AspectJ
  • Data access mechanisms provided by Spring
  • Integrating Hibernate with Spring
  • Spring MVC
  • Create a web application using Spring MVC
  • Apache tiles with Spring
  • Spring Web Flow
  • Keeping your application secure
  • Using log4j for logging
  • Writing test cases with JUnit
  • Spring Integration Framework

The course contents are:

  • Introduction to Spring
  • Spring Configurations
  • Aspect-Oriented Programming and DAO
  • Data Access
  • Spring Web
  • Integrating Struts2 and JSF with Spring
  • Spring Security
  • Spring Integration

Instructor: Industry Professional

Level: Intermediate

Duration: 4 weeks

User Review: 5/5

No. of Reviews: 9000

Price: $220.3

12. Spring Framework: Core Spring – Pluralsight

This is a learning path consisting of courses from beginner, intermediate and advanced levels. It is offered on the Pluralsight platform. In this training program, the learners will gain comprehensive programming knowledge and deepen their understanding of various configuration models for modern Java-based applications. 

The learners will also understand deployment platforms and how Spring makes it easier to create Java enterprise-level applications. 

In addition, the learners will understand the support components offered by the Spring framework, such as Kotlin and Groovy on the JVM. Next, the learners will explore how Spring provides more flexibility in development to create various forms of architectures depending on the application requirements. 

The course curriculum includes:

 

Beginner Level

Spring: The Big Picture

The first course of the beginner level provides a broader understanding of all aspects of Spring. It begins with the Spring fundamentals and exploring the basics of Sprint boot and the Spring framework. The learners will also cover the Spring related projects in-depth to gain a solid understanding of their implementations.

Spring Framework: Spring Fundamentals

The second program offers the concepts of building and configuring applications using the Spring Framework. The learners will discover concepts like dependency injection and auto wiring. Additionally, the learners will be able to convert legacy code to use the specific features of Spring.

Spring Framework: Creating Your First Spring Boot Application

In the final course of this level, the learners will cover the concepts of the Spring boot framework and how this framework ensures the scalability of Java applications. Moreover, the learners will be creating their first Spring boot application with two core aspects. In addition, the learners will gain insights into the architecture of Spring boot without containers or XML files.  Next, practical sessions allow learners to explore how to run pure Java applications on any environment supporting Java, including cloud platforms. 

Besides, the concepts of Spring boot starters for easy and faster integration with Spring technologies and third-party libraries or frameworks are covered in detail. Furthermore, the learners will also cover the concept of auto-configuration and the incorporation of data sources or REST services. 

Finally, there is also an in-depth session on Spring boot installation and its implementation for real-world applications., including the plugins that work with core Spring.

 

Intermediate Level

Spring Boot Fundamentals

This is an extended program that deals with the Spring framework to build simple web-based applications with lesser code and improve the development time. In this course, the learners can cover significant features associated with Spring boot, such as auto-configuration, Spring initializer, application development, data access, testing, Actuator, and GraphQL integration. Finally, the concepts on RESTFUL APIs are covered in-depth to give learners the idea about building production-ready applications.

Spring Framework: Spring Boot Actuator

In this tutorial, the learners will explore the uses of the Spring Boot Actuator and how to use them in production. First, the Spring Boot Actuator’s aspects that enable easy monitoring and managing applications in a production environment are covered with practical demonstrations.

Next, the learners will discover the built-in production-ready features that can be incorporated into the applications to reduce the developmental effort. Besides, the concepts on Actuator endpoints are explored in-depth.

 

Advanced Level

Spring Framework: Spring Expression Language (SpEL)

The first module of the advanced level provides an introduction to Spring expression language. The learners will understand the concepts of dynamic bean wiring and dependency injection. In addition, the concepts on how to leverage the power of SpEL for manipulating and query objects are covered thoroughly.

Furthermore, the learners will be familiar with implementing object graphs at runtime, which allows them to inject values to other beans dynamically. Finally, the concepts of conditionalization are explored in-depth.

Spring Framework: Aspect-Oriented Programming with Spring AOP

The course’s final module includes the advanced concepts of the Spring framework, such as AOP, and how they are implemented for building modular programs. Besides, the learners will also understand cross-cutting functionalities for various execution cases and learn how to design their Spring AOP.

Instructor: Dustin Schultz, Bryan Hansen, Dan Bunker, Kesha Williams, Buddhini Samarakkody, and Catalin Tudose

Level: Beginner/Intermediate/Advanced

Duration: 8 hours and 46 minutes

User Review: Beginner: 4.7/5, Intermediate: 4.6/5, Advanced: 4.6/5

No. of Reviews: 2143

Price: 10-Day Free Trial (Pricing available on Sign-Up)

Conclusion

The developers with programming skills and in-depth knowledge of the Spring framework are highly in demand due to their programming know-how and thorough exposure to the configuration models required for Java applications on an enterprise level.

According to Indeed reports, the Java Spring developers are offered an average base pay of $106,000 and a maximum of $121,151as per the location and the experience of the individuals in the USA. This salary trend illustrates the very high confidence of these developers with immense growth potential in their careers.

Therefore, aspirants and experienced developers aiming to deep dive into a career in web application development using Java and Spring framework should enhance their skill set with some of the top courses highlighted in this article.

With exposure to programming and theoretical aspects of the Spring framework and an industry-recognized certificate, it is highly likely to gain the position of top developers in the industry and embark on a successful career with lucrative salary structures.

Introduction

Students have to read through stacks and volumes of books and assigned text. In the past, the primary reference materials and assigned reading materials were printed books to be purchased or borrowed from a library.

Thanks to technology, these study materials are available in digital format. Those who prefer reading through a browser, using a computer, tablet, or smartphone can simply buy or rent these books. In contrast, those who like to read from printed materials can proceed with the traditional route of buying and/or borrowing. 

Among the youth, the use of gadgets is becoming the go-to option for studying and notetaking. They are digital natives who were born at a time when computers and other devices have become more sophisticated and user-friendly. As a result, they grow up knowing how to swipe and tap without reading a user manual. 

Related reading: Synchronous Learning vs. Asynchronous Learning – What’s the Difference?

Increasing Demand for Variety in Formats

Publishers have done a lot of work to ensure that there are options for online and offline reading. This reached a fever pitch during the start of the Covid-19 pandemic when schools demanded higher volumes of digital textbooks and reference materials instead of print materials. 

One of the goals of providing digital and print reading materials is to cater to students’ needs and preferences. In particular, having online materials is convenient because it can reach a more significant number of students in the field of education. In addition, there’s no need to worry about sourcing hard-to-find books and paying for shipping. Instead, everything happens with a few clicks. 

Linear and Non-Linear Reading 

Linear reading refers to the traditional way of reading (left to right, top to bottom), while non-linear reading is more scattered—going back and forth through pages, skimming through topics to grasp the subject matter

Everyone does both types of reading, whether you are doing it online or offline. Offline reading allows students to do both types of reading freely while only focusing on the material in their hands. Online reading, however, does so but in a limited sense.

If reading through a computer is also used for other purposes (writing, researching, entertainment), the attention span for reading is significantly reduced. Although different book formats present the same information, the manner or strategy by which a student consumes that information has to be different. These strategies will be discussed in a separate section. 

Reading Online 

Online learning has become a familiar and convenient way to acquire knowledge. Despite not being in an actual classroom, the students can have a learning experience through online classes (synchronous and asynchronous). Just like in traditional face-to-face learning, teachers give assigned reading lists.

In addition, however, teachers can simply provide links to source materials in an online setting, which is a very convenient option for those in an online class. 

One of the main challenges of those who study online is the eye strain due to reading from a screen. In addition, it causes fatigue for the eyes to the blue light. Another concern is that online reading is prone to distractions. 

Our brains are trained to scroll quickly through information when we’re on a digital platform, whether for leisure or study. This extends to online reading materials, and it results in a shallow understanding of the subject matter. However, online reading does have benefits. 

Benefits of Reading Online 

  • Convenient. Because these materials are available online, there is no need to go out and buy a book. For the same amount of money, students can access the same reference material without leaving the house. Some even include add-ons. 
  • Access. Online resources are available to anyone who has an internet connection and is granted access to materials. Before e-books were introduced, people had to worry whether the book they needed was available at their local library or bookstore. If not, they would have had to source it from abroad, paying for shipping and waiting a long time before getting a copy. 
  • Paperless and not bulky. The digital files will not take up space on a desk and add clutter to a room. More importantly, once a student has finished a school year, there is no need to worry about disposal. 
  • Bonus materials. Online resources often include hyperlinks for keywords and references, which students can access. Some even include links to videos, podcasts, and even the dictionary. This feature makes e-books and online references time-efficient. It also caters to the needs of different types of learners. 

Reading Offline 

Offline learning has always been the norm for acquiring knowledge as much as reading offline has been the norm for consuming information. Offline reading literally refers to any form of reading without the aid of the internet, but it usually refers to reading print materials such as a book.

Traditional reading techniques require students to get a book and to find a quiet corner for reading. When it comes to learning, it might require additional tools like pens, notebooks, and highlighters. Nevertheless, it is a straightforward approach. This analog approach is preferred by many because of its benefits.

Benefits of Reading Offline

  • In-depth learning. When students read from printed material, they focus on that one item before moving on to the next. This allows them to focus, contemplate and process the information before moving on.
  • Intentional. When reading print materials, you are only focusing on what is in front of you, which can be a great thing if you want to focus. In this way, all distractions from the text are eliminated (no hyperlinks and ads!). It’s up to the student to remove external distractions from their study area to fully reap the benefits of intentional reading and studying.
  • Interactive. The act of flipping through pages, annotating, and highlighting helps jog the mind. It engages the senses: sight, touch, even smell. Whereas in online reading, it’s mainly just the sense of sight that is engaged, offline reading adds a different layer of experience, which can help people retain and retrieve information.

Tips for Reading on a Screen 

In the syllabus or outline, students can find sources and links to online articles, online libraries, and e-books. Not only are online resources more convenient, but it is also said to be better for the environment. However, reading online requires a different approach. Here are some tips for online reading: 

  • Remove distractions. Consuming information from a gadget poses risks of getting distractions. Close all unnecessary apps, adjust the lighting on the device, and block all notifications. 
  • Identify your purpose. To avoid getting distracted, it might be a good idea to know why you are reading, and if possible, come up with questions. Let these questions guide you as you read through the article instead of aimlessly reading. 
  • Skim through. Read the title, the subheadings, and the first and last paragraphs to determine whether you have the right reading material. 
  • Take notes. Some e-book formats will allow you to annotate and highlight. However, it would also be a good idea to have a notebook on hand where you can take notes as you would while reading a printed book or listening to a lecture. This will help with retaining and retrieving information moving forward. 
  • Time limit. Read for 25-minutes, then rest the eyes for 5 minutes. Online reading exposes the eyes to blue light, which can lead to eye strain and fatigue.  

Which One Is Better for Studying? 

Online and offline reading each has their pros and cons. Online materials are easier to access and are more convenient, while offline materials are recommended for in-depth reading and annotating. Reading materials on paper has been proven to be very beneficial to learners as it engages different parts of the brain at once while reading. It helps the brain process information well. 

Reading strategy and skill play an essential role in learning, especially regarding online or digital materials. One cannot deploy the same reading techniques that they use when reading print materials to reading online. When reading online, people are vulnerable to distractions and mental exhaustion. Consider that when choosing between an e-book or a printed book for studying. 

Final Thoughts 

Reading online and reading offline allow students to consume information in different ways—that is to say, they are not substitutes for each other. The norm for reading has always reading offline.

However, reading online resources has allowed people from different parts of the world to access source materials without worrying about availability. In terms of studying, there is strong evidence that suggests that offline reading (specifically reading print materials) is still better for learning and information retention

Students these days reap the benefits of having options thanks to the developments in technology. 

Having access to reading materials has never been more convenient due to the availability of e-books and online libraries. Unlike what was initially feared, e-books have not replaced printed books.

In fact, reading materials in print and digital formats continue to be produced simultaneously. No one can argue that the most essential part is the content. In the spirit of sharing information, it all depends on which option is available and preferred by the people who will use it. 

Introduction

C++ is a cross-platform and general-purpose programming language used for creating high-performing applications. It is an extension of the C programming language and is more dynamic as it allows programmers with more control over the system, resources, and memory used for building applications. 

Today, C++ is one of the most popular programming languages implemented in major operating systems, graphical user interfaces, and embedded systems. Moreover, the C++ programming language provides a more precise structure of the codes, allowing code reusability that leads to lower developmental time and costs. 

As a result, C++ is one of the most sought-after skill sets among developers. C++ is one of the most sought-after skill sets among developers. In recent years, C++ has been used as a back-end technology and to build graphics-intensive applications, and it is used even for smartwatches which makes C++ is one of the most sought-after skill sets among developers. Therefore, aspirants must opt to upskill themselves with the help of some of the top trending courses on C++ on the online learning platform.

Related reading: Top 10 Java Online Courses

1. Coding for Everyone: C and C++ Specialization by University of California, Santa Cruz – Coursera

Coding for Everyone- C and C++ Specialization by University of California, Santa Cruz – Coursera

This specialization is offered on Coursera. In this course, the learners will cover the foundations of C and C++, learn to program in C, and move onto advanced programming concepts, including syntax in C++. Each module offers ample opportunities for learners to write programs to solve high-level problems with the help of algorithms and build complex games. 

In addition, the learners will understand how to find errors in codes and learn to debug them in a development environment. Numerous algorithms are covered in this training and essential topics such as graph theory and graph algorithms for a high-level understanding of the programming language. 

The course curriculum includes:

  • Programming Fundamentals
  • Structured Programming
  • C++ Part A and Part B

Instructor: Ira Pohl

Level: Beginner

Duration: 6 months

User Review: 4.4/5

No. of Reviews: 1227

Price: Free Enrollment (Additional charges for certification may apply)

2. Accelerated Computer Science Fundamentals Specialization by University of Illinois – Coursera

Accelerated Computer Science Fundamentals Specialization by University of Illinois – Coursera

This online program is available on Coursera. The certification course is designed for learners with prior experience in any programming language. It is entirely focused on providing learners with comprehensive knowledge about data structures and algorithms in C++. 

The learners will begin with the fundamentals of implementing data structures and learn about their efficiency in C++. Moreover, the learners will gain knowledge about object-oriented programming and asymptotic algorithms. Next, the advanced topics of data structures related to arrays, linked lists, trees, heaps, and graphs are covered in-depth. 

This online training prepares learners with well-developed coding skills and the know-how of the algorithms for building complex systems.

 The key takeaways from the course include:

  • Thorough understanding of object-oriented programming in the C++ language
  • Defining classes, encapsulation and data structures, and algorithms
  • Traversals, rebalancing, and shortest paths
  • Understanding of how to implement appropriate data structures in the best possible manner to solve a computational problem
  • Analyzing running time and space requirements for algorithms
  • Implementing data structures and algorithms for high-level system programming
  • Advanced library functions

The course modules are:

  • Object-oriented Data Structures in C++
  • Ordered Data Structures
  • Unordered Data Structures

Instructor: Wade Fagen-Ulmschneider

Level: Intermediate

Duration: 3 months

User Review: 4.7/5

No. of Reviews: 1803

Price: Free Enrollment (Additional charges for certification may apply)

3. Beginning C++ Programming- From Beginner to Beyond – Udemy

Beginning C++ Programming- From Beginner to Beyond – Udemy

This is one of the bestselling courses on Udemy to learn programming using C++. In this tutorial, there are no prerequisites, and the learners will begin with the fundamentals of the C++ programming language. 

The training program emphasized offering the modern C++ concepts rather than the older versions with several examples, practical demonstrations, coding challenges, and assignments for a thorough understanding of the programming language. 

Additionally, the learners will learn advanced features such as inheritance and polymorphism functions. 

At the end of the course, the learners will be well-equipped with the following skills:

  • In-depth knowledge of looping using while, do-while, for, and range based statements and recursion
  • Performing calculations and displaying the results
  • Functions and pointers
  • Classes and creating objects
  • Creating classes
  • Basic standard template library classes
  • Constructors and destructors
  • Copy and move semantics
  • Inheritance and polymorphism
  • Smart pointers and stream I/O
  • C++ STL and exception handling

The course curriculum includes:

  • Introduction
  • Installation and Setup
  • Structure of a C++ Program
  • Variables and Constants
  • Arrays and Vectors
  • Statements and Operators
  • Controlling Program Flow
  • Character and Strings
  • Functions
  • Pointers and References
  • OOP- Classes and Objects
  • Operator Overloading
  • Inheritance and Polymorphism
  • I/O and Streams
  • Exception Handling
  • STL and Lambda Expressions
  • Using Visual Studio Code
  • Enumerations

Instructor: Tim Buchalka and Dr. Frank Mitropoulos

Level: Beginner/ Intermediate

Duration: 45 hours and 59 minutes

User Review: 4.6/5

No. of Reviews: 40,866

Price: $69.6

4. The C++ 20 Masterclass: From Fundamentals to Advanced – Udemy

The C++ 20 Masterclass- From Fundamentals to Advanced – Udemy

The certification program boasts of an entirely new curriculum with modern C++ concepts for learners. It is available for enrollment on the Udemy platform. This training program offers learners the latest C++ concepts like ranges, coroutines, the three-way comparison infrastructure, and many more. 

The modules are well-designed and offer concepts so that learners can tackle the upcoming technologies in the industry to build an operating system with advanced features much like Windows, Mac, or Linux and develop complex software with shorter developmental cycles.

The learners will also explore how C++ is implemented for running devices such as embedded systems, electronic products, medical equipment, networking routers and switches, and powering industrial plants and manufacturing facilities.

Furthermore, the learners will have practical exposure to programming using advanced features such as function templates, class templates, polymorphism, move semantics, callbacks, STL containers, iterators, and various algorithms. The course modules are:

  • Introduction
  • Development Environment Installation and Setup
  • Variables and Data Types
  • Operations on Data
  • Literals and Constants
  • Data Conversions: Overflow and Underflow
  • Bitwise Operators
  • Variable Lifetime and Scope
  • Control Flow, Loops, Arrays, and Pointers
  • References and Strings
  • Functions and Enums and Type Aliases
  • Arguments to Main
  • Function Overloading and Lambda Functions
  • Function Call Stack and Debugging
  • Function Templates
  • C++20 Concepts: Classes, Objects and Const
  • Diving deep into Constructors and Initialization
  • Friends and Static Members
  • Programs with Multiple Files and Smart Pointers
  • Operator Overloading, Inheritance, and Polymorphism
  • Exception Handling and Box Container Class
  • Class Templates, Move Semantics, Function like Entities and STL Containers
  • STL Algorithms, C++20 Ranges and Range Algorithms
  • Building Custom Iterators

Instructor: Daniel Gakwaya

Level: Beginner/ Intermediate

Duration: 112 hours and 18 minutes

User Review: 4.7/5

No. of Reviews: 179

Price: $18

5. Become a C++ Developer Nanodegree Program – Udacity

This is a specialization course offered on Udacity. In this program, the learners will deep dive into the concepts of high-level programming using C++. In addition, the learners will explore concepts on how C++ is used for the most exciting innovations, such as self-driving cars, robotics, web browsers, social media platforms, servers, video games, and many more. This course emphasizes providing learners with hands-on experience in coding by working on real-world industry projects. 

Some of the essential projects offered include building a route planner using OpenStreetMap Data and developing a process monitor for the computer. However, there is a prerequisite in this program that requires learners to have intermediate knowledge of any programming language. Besides, the certification program offers technical mentor support, project review, and interaction with experienced industry experts. 

The course modules are:

C++ Foundations

In this module, the learners will explore how to develop and understand the compiling and executing process in C++ programming. Moreover, syntax functions, containers, and linking multiple files are some essentials that are covered in-depth.

Object-Oriented Programming (OOP)

The second module introduces learners to concepts on building classes, interfaces, and generic templates for creating an object-oriented C++ program. Besides, the learners will understand how to use tools for writing clean and reusable codes.

Memory Management

This module provides the learners with advanced concepts like controlling static and dynamic memory in C++ using resource acquisition, initializing patterns, pointers, references, and moving semantics

Concurrency

The fourth module focuses on introducing the concepts of execution paths in parallel in C++. Additionally, the learners will delve into concepts such as the launching process and threads to execute logic in parallel and advance to thread synchronization and communication. This module ensures that learners gain knowledge of the power of concurrent programming.

Capstone Project

The final module is the capstone project using all the core concepts covered to build an application using C++. The capstone is mandatory to attain the certificate of completion.

Instructor: David Silver, Stephen Welch, and Andreas Haja

Level: Intermediate

Duration: 4 months

User Review: 4.5/5

No. of Reviews: 1000

Price: $310.8/Per Month and $1056.8 for 4-Month Access

6. Advanced Programming in C++ by New York University – edX

Advanced Programming in C++ by New York University – edX

This online course is available on edX. In this program, the learners will gain knowledge on development using C++ programming. Advanced topics on command-line programs utilize functions, arrays, and strings to solve complex problems in a development environment. 

There are various hands-on sessions, bi-weekly quizzes, and lab challenges aimed at developing the programming skills of the learners. Furthermore, the learners will learn to use advanced procedural programming functionalities and analyze the computational complexities in coding.

 Finally, the learners will learn to build various computational models using multiple algorithms, focusing on controlling the time and storage required for such programs. The curriculum includes:

  • Function Analysis
    • Primality Testing
    • Runtime Analysis
    • Order of Growth
    • Asymptotic Analysis
  • Function Implementation
    • k-Combinations Problem
    • Flow of a Program
    • Runtime Stack Execution
    • Scope of Variables
    • Pass by Value
    • Parameter Passing
    • Function Lab Session
  • Arrays
    • Motivation
    • Computing the Average
    • Above the Average
    • Array Lab Session
  • Strings
  • Concatenating
  • Indexing
  • Slicing
  • Length
  • Comparing
  • Starting Index
  • String Lab Sessions
  • Final Exam

Instructor: Aspen Olmsted and Itay Tal

Level: Intermediate

Duration: 8 weeks

User Review: NA

No. of Reviews: NA

Price: Free Enrollment ($340 for verified track)

7. C++ Programming Course – Edureka

Edureka’s C++ programming course is designed to help learners build their skill set and practical experience to develop high-performance applications. The learners will explore concepts on building web browsers, game engines professionally. 

Besides, the advanced concepts on object-oriented programming using C++ and new coding styles and design patterns, generic programming, standard template library, optimized C++ code, C++ compiler toolchain, and STL algorithms and iterators are some of the key concepts covered in this training program. 

Additionally, the learners will delve into concepts like Hex and debugging options to ensure clean and error-free code development codes.  

The key takeaways from the course include:

  • In-depth knowledge of C++ data types, conditional statements, loops, multithreading, and exception handling
  • Object-oriented programming through C++, classes, and advanced concepts like abstract and final, and more
  • Understand industry standards and best practices
  • Coding styles, design patterns, and code reusability
  • Optimizing the code for improved performance
  • Understanding compiler toolchain and STL algorithms
  • Debugging and real-world industry project experience
  • Hex overview

Instructor: Industry professionals

Level: Beginner

Duration: Self-paced

User Review: 5/5

No. of Reviews: 1000

Price: $61.2

8. Programming in C++: A Hands-on Introduction Specialization by Codio – Coursera

Programming in C++- A Hands-on Introduction Specialization by Codio – Coursera

This course is offered on Coursera. It is intended for people seeking to learn to code for development using the C++ programming language. 

The course follows a hands-on approach towards learning that will allow them to pick up other programming languages like Java for the more advanced developmental experience. In the four modules of this training, the learners will begin from fundamentals to object-oriented design concepts. 

The hands-on sessions begin with smaller programs to perform repetitive tasks, and the learners will advance to building more extensive applications. 

The course curriculum includes:

  • C++ Basics: Selection and Iteration
  • C++ Basic Structures: Vectors, Pointers, Strings, and Files
  • C++ Object Basics: Functions, Recursion and Objects
  • Object-Oriented C++: Inheritance and Encapsulation

Instructor: Anh Le, Kevin Noelsaint, and Elise Deitrick

Level: Beginner

Duration: 4 months

User Review: 4.5/5

No. of Reviews: 146

Price: Free Enrollment (Additional charges for certification may apply)

9. Learn Advanced C++ Programming – Udemy

Learn Advanced C++ Programming – Udemy

This certification program is available on Udemy. In this course, the learners will delve into advanced concepts and features of the C++ programming language. 

First, the learners will deepen their knowledge of basic C++ as a refresher, followed by C++ 11 features, and explore the concepts of file handling, STL template classes, operator overloading, lambda expressions, and constructors thoroughly. 

At the end of the course, the learners will create programs for generating fractal images and work on application building using features like smart pointers and arrays. 

The course curriculum includes:

  • Introduction
  • Exceptions and Files
  • Standard Template Library
  • Operator Overloading
  • Passing Functions to Functions
  • C++11 Additional New Features
  • GUI Programming in C++
  • Project

Instructor: John Purcell

Level: Intermediate/Advanced

Duration: 15 hours and 11 minutes

User Review: 4.5/5

No. of Reviews: 7042

Price: $30.4

10. C++ Learning Path – Pluralsight

This learning path comprises multiple courses ranging from beginner to advanced. It is available on Pluralsight. The beginner programs provide a gentle introduction to programming with C++.

All the fundamental concepts are covered in detail, and the learners can expect to be confident with writing basic codes for developing smaller applications and be familiar with the features of C++. Next, the learning path provides intermediate courses to grasp the designing principles using C++. 

In addition, the learners will understand how to write functional and clean codes with the help of data structures and algorithms and the C++ standard library.  The advanced training modules focus on refining the learners’ skills with prior experience with C++ programming. The learners will explore advanced features and techniques and learn to write unit tests for the C++ codes.

Finally, the learners will expand their knowledge on the C++ toolkits for writing high-performance and concurrent C++ programs. By the end of the course, the learners will have solid programming experience and an in-depth understanding of the following concepts:

Operators

Objects and Classes

Flow of Control

References and Polymorphism

Inheritance

C++ Type System

Heap Stack Semantics

Stream I/O

Overloading

Lambdas

Exceptions and Scope Management

Templates and C++ Standard Library

Concurrency

The learning path provides the following courses:

Beginner Courses

Learn to Program with C++

This course aims at building programming skills for absolute beginners. First, the basic concepts of C++ and syntax are covered in depth. Next, the learners will delve into the tools to develop in C++ and the basics of developing and running an application. Finally, the learners will discover how to write and use functions and classes in programming and the effectiveness of the C++ standard library.

C++ Fundamentals Including C++17

In this program, the learners will expand their basic knowledge and deep dive into writing simple console applications and advancing to writing platform-specific codes. In addition, the learners will have a thorough understanding of concepts like declaring variables, classes, building expressions with the help of operators and functions in C++, and understanding the uses of templates, indirection, and polymorphism.

Practical C++14 and C++17 Features

This course focuses on building the learners’ practical knowledge and gaining more profound knowledge about using various features of C++ for improving the performance of the programs.

Some of the key topics include digit separators, polymorphism Lambdas, and constexpr functions. The learners will also gain insight into the improvements introduced in the C++ standard library, such as standard–defined suffixes for the Chrono library and more.

Finally, the learners will explore new and practical features such as nested namespace and structured bindings. There are sufficient demonstrations and follow-along exercises for learners to develop their programming skills with new features.

At the end of the course, the learners will be able to write simpler and clearer codes that are efficient and deliver high performance. However, the prerequisite requires a basic understanding of C++ programming to understand the new features more clearly.

Intermediate Courses

C++17: Beyond the Basics

This course focuses on intermediate learners with prior programming experience. The learners will move beyond the basics and understand concepts about modern C++ and its features. First, the learners will begin with the concept of standard library collection classes and the functions and algorithms that make codes easier to interpret.

Furthermore, the learners will discover the usefulness of Lambdas and how to use move semantics for enhanced performance.

Reading Legacy C++

The course covers the essentials of C++, such as library functions and the best practices in modern C++. The learners will gain the ability to understand old codes and find the relevant differences with modern C++ codes.

The learners will gain knowledge about C-style arrays and C-style strings. Next, the learners will cover the topics on macros, typedefs, and old constructs. Finally, the learners will explore the concepts on printf. and format strings.

Introduction to Data Structures and Algorithms in C++

This course introduces data structure and algorithms and how they are used to make coding easier in C++. The program offers both theoretical and practical aspects of the concepts.

The learners will begin with concepts like C++ class and arrays in programming, including automatic memory management with the help of constructors and destructors.

Additionally, the learners will deep dive into operator overloading and optimizing the array class with move semantics. The learners will also explore the concepts of generalizing array class with templates, Big O notation, search algorithms, and data structures such as stack with LIFO policy and push and pop operations, and more.

C++ Standard Library: Sequential Containers

In this tutorial, the learners will delve into concepts such as storing sequences of elements, vector containers, standard algorithms, inserting, removing, and searching elements, and encapsulation. Finally, the learners will understand how to use high-quality and well-tested C++ standard library containers in programming.

C++ Standard Library: Associate Containers

This is an extended course from the previous program on sequential containers and covers essential concepts like storing unique objects, mapping unique keys to values, and efficient key-value associations required in development.

Beautiful C++: STL Algorithms

This tutorial covers important concepts on standard libraries in C++ and topics like using the algorithm header. The learners will explore how iterators can help to multiply the power of the library. In addition, the learners will be familiar with concepts like using the same algorithms with various collections to avoid learning new functions each time during developing applications.

Beautiful C++: Updating Legacy Code

The final program in the intermediate level focuses on introducing learnings to compiler, the changes in C++14 and 17, using the standard library for efficiency and evaluating the performance of the applications by leveraging the library capabilities.

Advanced Courses

C++ Unit Testing Fundamentals Using Catch2

This course offers the fundamentals of unit testing in C++, followed by advanced concepts on unit testing frameworks. There is an introductory module on unit testing using Catch, organizing the tests with Catch, asserting, and handing duplicate codes. The emphasis is on allowing learners to be familiar with writing better and cleaner C++ codes for reusability.

Advanced C++ Mocking Using Google Mock

The second module of the advanced level focuses on introducing unit testing with the help of the Google test. Next, the learners will explore the mocking frameworks and the best practices. Finally, the learners will explore the concepts on unit testing patterns for legacy codes.

High-Performance Computing in C++

The final course allows learners to code and scales them across CPU registers and multi-cores, including various machine clusters. In addition, the learners will delve into the concepts related to single instruction, multiple data, open multi-processing, message passing interface, C++ accelerated massive parallelism, and generative art demo.

These concepts are beneficial for experienced programmers aiming for senior career roles as developers and project managers.

Instructor: Kate Gregory, Giovanni Dicanio, Dror Helper, and Dimitri Nesteruk

Level: Beginner/Intermediate/Advanced

Duration: 15 hours and 11 minutes

User Review: Beginner: 4.7/5, Intermediate: 4.8/5, Advanced:

No. of Reviews: 1339

Price: 10-Day Free Trial (Pricing available on Sign-Up)

Conclusion

Learning a C++ programming language is an excellent platform to begin a developer’s career. Besides, C++ developers build their skills with solid foundations such as data structures and algorithm concepts which provides them a high-level understanding of modern programming languages. Furthermore, C++ developers are also considered vital for an organization as they are associated with developing multiple systems beyond the standard software development regime.

Today, C++ developers continue to be among the highest-paid jobs in the industry. As the C++ developers’ demand continues to rise, it is the most opportune moment for all the aspirants to equip themselves with C++ language skills and embark on a successful career path as top developers in the industry.

Introduction

In the past decades, a career in statistics was primarily associated with an academic job in the university. However, with several multi-disciplinary advances, data has become a vital component for successful operations. 

In addition, the emergence of several sub-branches such as data science and big data and machine learning plays an integral part in organizations across industries to derive meaningful insights from an enormous amount of data generated every day. From universities, sports professionals, finance, healthcare, engineering, technology, marketing and advertising, and e-commerce, statisticians are highly in demand to provide a competitive advantage. 

With an expected growth rate of 33%, the U.S Bureau of Labor Statistics has highlighted the job trend for statisticians to grow faster than most occupations. Therefore, with increasing opportunities, it is the opportune moment for aspirants to upskill themselves and deep dive into a successful career in some of the most trending industries.

Related reading: Top 13 Online Courses to Learn Data Analysis

1. Become a Probability and Statistics Master – Udemy

Become a Probability and Statistics Master – Udemy

This is one of the bestselling courses on statistics on the Udemy platform. The course allows participants to build comprehensive knowledge with concepts ranging from the fundamentals to the most advanced concepts spanning 163 lessons, including demonstrations, text explanations, quizzes, and assignments.

The key takeaways from the course include:

  • Data visualization using bar graphs, pie charts, histograms, and plots.
  • Analyzing data using mean, median, mode, and IQR.
  • Data distributions and probability including mean, variance, and standard deviation.
  • Bayes theorem, union and intersections, and independent and dependent events.
  • Discrete random variables, Poisson, and geometric random variables.
  • Sampling and types of studies, bias, confidence intervals.
  • Hypothesis testing, statistical inference analysis, significance levels, and test statistics.
  • P-values, regression, scatter plots and correlation coefficients, and chi-square.

The course curriculum includes:

  • Getting started
  • Visualizing data
  • Analyzing data
  • Probability
  • Discrete random variables
  • Sampling
  • Hypothesis testing and regression
  • Final exam and wrap-up

Instructor: Krista King

Level: Beginner

Duration: 14 hours and 21 minutes

User Review: 4.7/5

No. of Reviews: 7747

Price: $47.8

2. Introduction to Statistics by Stanford University – Coursera

Introduction to Statistics by Stanford University – Coursera

This course is available on Coursera. This training program focuses on building solid foundational statistical skills for learners to work with data and communicate insights effectively. This course’s key topics are descriptive statistics, sampling and randomized controlled experiments, probability, sampling distributions, and central limit theorem. 

In addition, some of the essential components such as regression, a common test of significance, and resampling are covered in-depth. At the end of the course, the learners will learn data analysis, differentiate between descriptive statistics and prescriptive statistical concepts, work with data sets, and select proper tests for multiple contexts. 

The concepts covered in the course are sufficient for learners aiming to pursue advanced statistical analysis and machine learning courses. 

The curriculum includes:

  • Introduction and descriptive statistics for exploring data
  • Producing data and sampling
  • Probability
  • Normal approximation and binomial distribution
  • Sampling distributions and central limit theorem
  • Regression, confidence intervals, and tests of significance
  • Resampling and analysis of categorical data
  • One-way analysis of variance (ANOVA) and multiple comparisons

Instructor: Guenther Walther

Level: Beginner

Duration: 15 hours

User Review: 4.6/5

No. of Reviews: 405

Price: Free Enrollment (Additional charges for certification may apply)

3. Statistics for Data Science and Business Analysis – Udemy

Statistics for Data Science and Business Analysis – Udemy

This online program is offered on Udemy. In this course, the learners will learn to understand complicated statistical problems and analysis in an organizational environment. 

The program offers easy-to-understand concepts with plenty of practical assignments, additional resources and introduces all the necessary statistical lingo. Furthermore, the learners will explore the concepts of data visualization and critical statistical concepts required for a data scientist and data analyst to provide insights from large volumes of data. At the end of the course, the learners will be well-equipped to know statistical fundamentals, plotting various data types, correlation and covariance, confidence intervals, and making data-driven decisions.

 In addition, the learners will gain a basic understanding of how to use a programming language like Python and R to perform hypothesis testing, regression analysis, and other statistical measures to work with different types of data distributions and variables. 

The course contents are:

  • Introduction
  • Sample or population data
  • The fundamentals of descriptive statistics
  • Measures of central tendency, asymmetry, and variability
  • Practical examples
  • Distributions
  • Estimators and estimates
  • Hypothesis testing and fundamentals of regression analysis
  • Assumptions for linear regression analysis

Instructor: 365 Careers Team

Level: Beginner

Duration: 4 hours 51 minutes

User Review: 4.6/5

No. of Reviews: 26,029

Price: $47.8

4. Practical Statistics – Udacity

Practical Statistics – Udacity

This online certification program is available on Udacity. The course aims to build foundational skills in statistics to analyze data. Furthermore, the learners will understand the modern use cases and learn about the techniques to tackle real-world challenges. 

In addition, the learners will explore the concepts on A.B. tests and build regression models using programming languages such as Python and SQL. The prerequisites of this program include working knowledge with SQL, Python, and the libraries such as Pandas or NumPy to perform data analysis. 

The course modules are:

  • Simpson’s paradox
  • Binomial distribution
  • Bayes rule
  • Sampling distributions and central limit theorem
  • Hypothesis testing
  • T-tests and A/B tests
  • Logistic regression
  • Course project

Instructor: Josh Bernhard, Sebastian Thrun, Derek Steer, Juno Lee, Mike Yi, David Venturi, and Sam Nelson

Level: Intermediate

Duration: 35 hours

User Review: N.A.

No. of Reviews: NA

Price: $310/month

5. Advanced Statistics for Data Science Specialization by John Hopkins University – Coursera

Advanced Statistics for Data Science Specialization by John Hopkins University – Coursera

This is a specialization course available on Coursera. The certification program offers fundamental concepts in probability and statistics in the initial modules. There is also a mathematical statistics bootcamp that covers the concepts and methods used in biostatistics applications. 

Additionally, the learners will explore the advanced concepts of linear models, modeling tools in data science, least-square and linear regression, hypothesis testing, likelihood concepts, and distribution. Next, the learners will deep dive into the models’ practical implementations to perform multivariate regression using the R programming language. 

The course also builds a strong foundation in linear algebraic requirements for data science and the mathematical perspective of linear statistical models. 

The curriculum includes:

  • Mathematical biostatistics boot camp 1 and 2
  • Advanced linear models for data science
  • Least-squares
  • Statistical linear models

Instructor: Brian Caffo

Level: Advanced

Duration: 5 months

User Review: 4.5/5

No. of Reviews: 111

Price: Free Enrollment (Additional charges for certification may apply)

6. Probability and Statistics for Business and Data Science – Udemy

Probability and Statistics for Business and Data Science – Udemy

This certification course is available on Udemy. The training program offers concepts on probability and statistics from a business and data science perspective. The learners will cover the theoretical aspects and the implementations of statistics in real-world problems. 

Additionally, the learners will explore the basics of data and understand how to analyze data with various statistical measurements such as central tendency, dispersion, and understanding how bivariate data sources are associated with each other. Furthermore, the learners will delve into the concepts of probability, the combinations and permutations, and conditional probability and using the Bayes theorem. 

Besides, the concepts of distributions are covered in-depth. Finally, the learners will cover a few advanced topics such as ANOVA, regression analysis, and chi-square analysis. The course contents are:

  • Measurements of Data
  • Mean, Median, and Mode
  • Variance and Standard Deviation
  • Covariance and Correlation
  • Permutations and Combinations
  • Unions and Intersections
  • Conditional Probability
  • Bayes Theorem
  • Binomial Distribution
  • Poisson Distribution
  • Normal Distribution
  • Sampling
  • Central Limit Theorem
  • Hypothesis Testing
  • T-Distribution Testing
  • Regression Analysis
  • ANOVA
  • Chi-Squared

Instructor: Jose Portilla

Level: Beginner/Intermediate

Duration: 5 hours and 14 minutes

User Review: 4.6/5

No. of Reviews: 4531

Price: $47.8

7. Statistics with R Specialization by Duke University – Coursera

Statistics with R Specialization by Duke University – Coursera

This is among the highly rated online courses on statistics on Coursera. The training program offers critical data analysis and visualization concepts using R and how to create reproducible analytical reports. Additionally, the learners will understand how to perform statistical inference, Bayesian statistical inference, and modeling to make data-based decisions. 

Besides, the learners will understand how to communicate statistical results effectively and evaluate the data-driven decisions, including data wrangling with R packages for performing data analysis. 

The course modules are:

  • Introduction to probability and data with R
  • Inferential statistics
  • Linear regression and modeling
  • Bayesian
  • Statistics with R Capstone

Instructor: Mine Cetinkaya- Rundel

Level: Beginner

Duration: 7 months

User Review: 4.6/5

No. of Reviews: 5132

Price: Free Enrollment (Additional charges for certification may apply)

8. Data Analysis and Fundamental Statistics – Futurelearn

Data Analysis and Fundamental Statistics – Futurelearn

The certification program is offered on the Futurelearn platform. In this program, the learners will begin with statistics and expand their knowledge of data analysis using Excel. 

In addition, some of the essential tools and techniques to perform data analysis using Excel formula to achieve various objectives such as importing, cleaning, analyzing, and data manipulation. Furthermore, the learners will delve into the fundamentals of statistics using machine learning and learn the basic statistical principles. 

The course also offers additional mathematical concepts to build solid statistical skills for data analysis. Upon completing the course, the learners will have solid foundations of data analytics and statistics, the tools and techniques and their implementation, data processing tools for business decisions, and advanced Excel techniques to perform statistical analysis from an extensive database.

Instructor: Jacques Haasbroek

Level: Beginner

Duration: 4 weeks

User Review: N.A.

No. of Reviews: NA

Price: $39/month

9. Micromasters Program in Statistics and Data Science by MIT – edX

The Micromasters program is a specialization on the edX platform. This program comprises four modules and a virtually proctored exam. The learners can expect to master the skills of the methods and tools used in data science and machine learning for performing data analysis.

 Additionally, the learners will explore the fundamentals of probability and statistics and learn to implement and experiment with various data analysis techniques and machine learning algorithms. However, there are some prerequisites for the course that include understanding calculus and mathematical reasoning and a basic understanding of Python programming. 

The takeaways from the course include:

  • Mastering the foundations for data science, statistics, and machine learning
  • Analyzing big data and derive insights for business decisions with probabilistic modeling
  • Statistical inference and identifying methodologies, and deploying appropriate models
  • Develop machine learning algorithms to work with unstructured data and learn popular unsupervised learning methods.
  • Basics of deep neural networks, clustered methodologies, and supervised methods.

The course contents are:

  • Probability: The science of uncertainty and data
  • Fundamentals of statistics
  • Machine learning with Python: From linear models to Deep learning
  • Capstone

Electives:

  • Data analysis in social science: Assessing your knowledge
  • Data analysis: Statistical modeling and computation in applications

Instructor: Regina Barzilay, Eren Can Kizildag, Sara Fisher Ellison, Jan-Christian Hutter, Patrick Jaillet, Jagdish Ramakrishnan, Katie Szeto, Kuang Xu, Dimitri Bertsekas, Esther Duflo, Qing He, Tommi Jaakkola, Jimmy Li, Philippe Rigollet and John Tsitsiklis

Level: Intermediate/Advanced

Duration: 1 year 2 months

User Review: N.A.

No. of Reviews: N.A.

Price: $1528

10. Statistics with Python Specialization by University of Michigan – Coursera

Statistics with Python Specialization by University of Michigan – Coursera

This course is available on Coursera. The specialization is designed to teach learners various concepts of statistical analysis using the Python programming language. The learners will understand the data sources, types of data, and the process of collecting, studying, and managing data. 

Furthermore, the learners will understand the techniques of data exploration and visualization. In addition, the learners will deep dive into the data assessment theories, construct confidence interval concepts, and interpret inferential results. Besides, advanced statistical modeling procedures are covered in-depth with practical hands-on sessions to master the skills.

 Finally, the learners will understand research questions and connect them to the statistical and data analysis methods to deal with complex problems in a real-world scenario. The course modules are:

Understanding and visualizing data with Python

This module introduces the field of statistics, data sources, study design, and data management aspects of a data science problem.

In addition, the learners will explore the data and communicate the findings with data visualization techniques. The learners will have a solid understanding of various data types and interpret univariate and multivariate data summaries.

 The module also covers important concepts on probability and non-probability sampling of large populations and learns how each sample varies and how inference can be applied based on probability sampling.

Finally, the learners will apply the statistical concepts using Python during lab sessions and implement various libraries to perform data analysis.

Inferential statistical analysis with Python

The second module focuses on the basic principles behind data for estimation and assessment. First, the learners will analyze categorical and quantitative data, population techniques, and expand to handle two populations. Next, the learners will understand how to use confidence intervals and work with sample data to assess whether specific parameters are consistent within the data set. 

Finally, the learners will learn about interpreting inferential results and work on numerous case studies to solidify their skills by implementing statistical concepts using Python.

Fitting statistical models to data with Python

The course’s final module explores the advanced concepts on statistical inference techniques and learns to fit statistical models to data correctly. In addition, the learners will work on various models and understand the relationship between variables for predictions. 

This module also introduces and explores several statistical modeling techniques such as linear regression, logistic regression, generalized linear models, Bayesian techniques, and hierarchical and mixed-effects models. All of the concepts covered in the module are demonstrated with the help of practical examples using real data sets. Besides, the learners will understand the types of modeling approaches available for different data types based on the underlying study design. 

Finally, the learners will explore data visualization using Python and various libraries such as Statsmodels, Pandas, and Seaborn for advanced statistical analysis.

Instructor: Brenda Gunderson, Kerby Shedden, and Brady T. West

Level: Beginner

Duration: 3 months

User Review: 4.6/5

No. of Reviews: 2220

Price: Free Enrollment (Additional charges for certification may apply)

11. Data Science: Statistics and Machine Learning Specialization by Johns Hopkins University – Coursera

Data Science- Statistics and Machine Learning Specialization by Johns Hopkins University – Coursera

This online course is offered on Coursera. The training program is ideal for learners with a basic understanding of statistics and machine learning. It covers concepts on statistical inference, regression models, and machine learning algorithms for data analysis.

The learners will also understand how to develop data products using various tools and techniques and work with real-world data. 

In addition, the learners will also have a thorough understanding of building and applying prediction functions and applying advanced statistics to conclude populations and scientific insights from the data. The course contents are:

Statistical inference

In this module, the learners will understand how to draw conclusions about populations and perform various inferences, including statistical modeling and data-related strategies. Moreover, the learners will understand the uses of designs and randomization in data analysis and the broad theories of frequentists, Bayesian, and Likelihood. In addition, the learners will explore various complexities faced with missing data, observed and unobserved confounding, and bias while handling data.

Regression models

The second module explores the linear models for assumptions, regression models, and a subset of linear models. Furthermore, the learners will explore the statistical analysis tools for modern data scientists and cover many concepts, including regression analysis, least-square, and inference using statistical models.

Besides, the learners will delve into advanced concepts and learn to use ANOVA test and analysis of residuals and variability and building scatterplots for presenting analytical reports.

Practical machine learning

This module covers the essential components of building a prediction function on practical applications. The learners will explore the concepts of training and test data sets, overfitting, and error rates associated with computational models. In addition, the basics of the range of a model and essential machine learning algorithms such as regression. Classification trees, Naïve Bayes, and random forests are covered in-depth with hands-on lab sessions.

Data science capstone

The final module is mandatory for learners as the capstone requires creating usable and public data products from real-world problems in collaboration with industry, government, or academic partners. The learners are required to clear the capstone to attain the certificate of completion.

Instructor: Brian Caffo, Jeff Leek, and Roger D. Peng

Level: Intermediate

Duration: 6 months

User Review: 4.6/5

No. of Reviews: 484

Price: Free Enrollment (Additional charges for certification may apply)

12. Statistics Essentials for Analytics – Edureka

This is a self-paced course offered by Edureka. In this course, the learners will cover the fundamental concepts of statistics from a data science perspective. All the concepts are designed in detail that is in sync with the statistical and probability requirements to deal with data-related problems in data science. 

The learners will learn about data and its types and various statistical sampling procedures to analyze data efficiently. In addition, the learners will cover advanced concepts on statistical inference, testing and clustering, and various machine learning algorithms that have been found effective in handling data-related complexities. 

The key takeaways from the course include:

  • Thorough understanding of data and data types
  • Mastering sampling techniques
  • Descriptive statistics
  • Applying a probabilistic approach to solve complex problems
  • A/B Testing and parametric and non-parametric testing
  • Experimental designing
  • Parametric test types
  • Bayesian inference
  • Understanding clustering techniques
  • Regression modeling
  • Hypothesis testing
  • Machine learning fundamentals

Instructor: Industry Professionals

Level: Intermediate

Duration: Self-Paced

User Review: 5/5

No. of Reviews: 6000

Price: $81.6

Conclusion

In the current scenario of continuous innovations, the competition in the industries is sky-high. On the other hand, millions of data are being generated every day from various sources.

Although several new technologies have aided in faster data analysis, statistics experts remain an asset for various organizations. In the new era of data-driven decisions, deriving meaningful insights from them to generate business decisions to achieve business goals has become vital in all industries. 

From weather forecasting, finances, insurance, sports, supply chain, manufacturing, government agencies, life sciences to healthcare, data has gained prime importance, and appropriate analysis of data can provide significant knowledge about evaluating performance and building future strategies to tackle challenges or to gain competitive advantage in the market.

In addition, multi-disciplinary fields such as data science and big data have generated a high demand for statistics professionals. 

To build a career as a successful statistics professional in multi-disciplinary industries requires upskilling with the appropriate theoretical and practical skills. Thus, it becomes essential to opt for online courses that provide exposure to all the necessary skills and provide industry-recognized certificates to showcase the individuals’ skills. Therefore, the article highlighted some of the top trending courses on statistics on online platforms.

Introduction 

Modern technology and the changing demands of students have forced educational institutions to find ways to deliver education. To this day, the norm is to have students enroll in classes and attend them on campus in a face-to-face setup. This is a widely practiced and accepted method of teaching. The education industry has learned to slowly adapt because of the internet and fast-developing technologies. 

eLearning has been heavily utilized by universities to deliver graduate, postgraduate and non-degree programs. Delivery through an online course was convenient because students at the graduate and postgraduate levels usually have full-time jobs. Therefore, schools had to find a way to deliver a curriculum that did not disrupt the students’ working lives. Some online homeschooling programs are available, but the preference of the majority has always been in-person instruction. 

A new and different approach—the blended learning approach is being utilized for students of all levels. Some call it hybrid learning because it combines principles of online learning and face-to-face classes.

The blended learning system provides a structure for learning. Like in face-to-face classes, there are goals, requirements, and assessments the students have to comply with. Although it’s more flexible and convenient, schools have ways to ensure that the students meet these goals and minimum requirements in order to move up a grade level. 

Related reading: 10 Steps for Successful Online Learning

Blended Learning vs. Traditional Classroom Setup 

There is some debate as to which one is better between blended learning and traditional face-to-face classes. Face-to-face classes allow students to have real-time interaction and engagement with their peers. 

Schools set the routines for students: show up to school, have a morning break, back to class, have lunch, have afternoon classes, go home, and do homework. This routine is one that even our parents and grandparents grew up knowing. This method has allowed people to live more or less regimented lives. 

eLearning does not take place in a classroom. It can happen at home, at a foreign country, at a relative’s vacation house, or at a cafe. Students follow the curriculum set by the school, but learning goes beyond the four walls of the classroom

In both cases, the course content is delivered and is meant to ensure a complete learning experience for students. The main difference between the two is that of the learning platform. – one through the traditional classroom setup, the other in front of the computer. 

How Blended Learning Works 

Blended learning requires careful outlining of the course content, planning assessments while making sure that these are aligned with students’ developmental and learning goals. There is no fixed formula for the number of times students and teachers have to meet face to face versus the amount of time on eLearning platforms. However, here are some guidelines to follow: 

  • A schedule of face-to-face classes will be set in advance. All students are expected to attend 
  • During face-to-face sessions, teachers will take the lead.
  • For eLearning sessions, teachers may deliver lessons through webinars, online lectures, or making activities that students could do independently or in groups.
  • During blended learning, sessions may be conducted through synchronous or asynchronous sessions.

And so, to be able to deliver lessons effectively, there needs to be a blended learning model –a framework—to serve as a guide. Blended learning is practical and flexible, but it’s not a free-for-all. Students should not miss any learning milestones, and teachers have to be on their toes, making sure that they have enough tools and creativity to come up with engaging lesson plans. 

Be Patient with the Transition 

Having a solid learning management system will be advantageous to the extent that it will help manage and execute learning and teaching strategies for a specific course. Instructors who are trained in the traditional teaching principles and methods should reconsider the tools and strategies that they deployed in face-to-face classes; some of them might work in the online learning setup.  

Benefits of Blended Learning 

This hybrid of both the traditional and eLearning methods allows all students to experience the best of both approaches. However, teachers still take the lead by providing the course structure—they determine how often they should meet face-to-face while allowing students to have the freedom to study on their own. 

Blended learning allows students to have a deeper understanding of course material because they learn at their own pace. They can devote an extra hour to reading a challenging text or solving a series of complex word problems as needed. On the flip side, they can move on quickly from a topic or that they were able to complete in a short amount of time

Blended learning empowers students to take responsibility for their education. By working independently, students develop a work ethic and attitude that can help them transition into university and/or professional working life. 

A common misconception of self-paced learning is the belief that students will procrastinate—put off studying only when it’s convenient. If anything, students have to learn self-management and self-discipline, both of which are essential life skills. Students still have to comply with requirements and take exams and assessments. To prepare for these, students have to be intentional with setting a study schedule to keep up with the demands of school, while preventing procrastination and burnout. 

Additional benefits: 

  • Takes the best practices of both online classes and face-to-face classes and allows students to have a more personalized learning experience.  
  • Blended learning provides the opportunity to explore various learning tools that can be used to facilitate students’ face-to-face and online learning experiences.  
  • Teachers are encouraged to expand their beliefs and skills about their role in educating students. 
  • It is convenient and flexible for students and teachers. 
  • Blended learning caters to the needs of different types of learners. Some students learn best from a structured environment. Other students can learn independently. 
  • Students and teachers are working towards clearly set goals while exploring different ways to achieve them. 

Best Practices

There has to be a system and structure in place to implement blended learning effectively. Here are some of the best practices that teachers, students, and school administration can do to maximize the benefits of blended learning. 

For Teachers: 

  • Explain the structure of the blended learning setup. This is meant to set the tone for the entire course. Explain the course outline, the dates of face-to-face classes, and the various ways to keep in touch. 
  • Prepare a variety of activities. Use quizzes, games, group activities using tools that can engage students. A lot of information is already available through the internet, so the last thing the students need is a lecture that will only repeat something they could have picked up on the internet. 
  • Explore all forms of media. Use apps and social media tools as needed, being mindful that while it can engage students, it could also be a source of distraction. Use with caution. 
  • Keep communication lines open, but set boundaries. Blended learning means not meeting with students daily. As such, keeping in touch is very important. Meanwhile, avoid sending emails late at night and on weekends. Try to be mindful of professional communication etiquette with students.   

For Department Heads and School Administration: 

  • Invest in a good learning management system (LMS).
  • Train the teachers and non-teaching staff (like school counselors) on how to use the LMS. Emphasize the benefits and practical use of this system. 
  • Conduct regular alignment meetings to assess and troubleshoot the system. 

For Students: 

  • Raise concerns about the setup, schedules, and content so that they can be addressed early on. 
  • Create a routine and structure. Blended learning means being able to learn at your own pace. To reap the benefits of this learning setup, students have to have a routine that will keep their minds alert and awake to do the school work. 
  • Get rid of distractions. It’s easy to get distracted when there are no teachers to monitor students’ behavior. This goes hand in hand with following a routine. When a student is at their study area, they have to remove any distraction to be able to focus on their school-related tasks, before proceeding to other activities. 

Is this the Future of Education? 

In the past, eLearning and online classes were presented as options for students who could not make it to class. However, universities limited these options to working students and those who may be abroad. 

However, the Covid-19 pandemic has forced the entire education system of different countries to adapt and explore more flexible methods. At first, all classes had to be conducted online, but as the world learns to live with the virus and schools start to reopen, they need to be prepared should campus closures occur. 

Depending on where you are in the world, schools that have opened may limit the number of students in a classroom, therefore at some point, students and teachers have to get used to the blended learning system environment. So schools may close, but learning should not stop. 

Final Thoughts 

Blended learning provides a learning experience that caters to the needs of different types of learners. By combining elements of face-to-face teaching and eLearning, students get the best of both worlds. Likewise, teachers are able to explore a different type of teaching.

Teachers and instructors are forced to reevaluate their strategies and methods (which may have focused on face-to-face and classroom instruction). Overall, blended learning is a step toward the future of teaching and learning. 

Introduction

Data analysis is the science of analyzing data by various processes such as data cleaning, data transformation, and modeling data for discovering meaningful insights for business decisions. In recent years, data has become the “new oil” of the industry, and examining data ensures organizations obtain precise information to direct their operations to achieve the business objectives. 

From identifying demographic groups and addressing their needs, identifying patterns to predicting actions for problems areas, and uncovering business opportunities, the job of a data analyst has become the core of every business thriving to achieve competitive advantage in the market. Moreover, with data analysis encompassing several opportunities, the job roles have become more exciting. 

Today, the data analysis industry has various exciting career prospects as a data scientist, machine learning engineers, data engineers, and many more and this trend continues to evolve each year. Therefore, aspirants and experienced professionals aiming for a future-proof career should upskill themselves with the appropriate skills to dive into a lucrative career with tremendous job satisfaction and growth.

Related reading: Top 15 Online Courses to Learn Python

1. Data Analysis and Visualization Foundations Specialization by IBM – Coursera

Data Analysis and Visualization Foundations Specialization by IBM – Coursera

This course on Coursera is one of the essentials for beginners to learn data analysis. In this specialization, the learners will be prepared for a data-driven transformation by understanding the core principle of data analysis. Moreover, they will cover the concepts of deriving insights from data and communicating the findings and the data visualization techniques for a better presentation of data. 

In addition, the learners will explore the tools with multiple hands-on sessions to work on data discovery effectively. Furthermore, the concepts of the modern data ecosystem comprising databases and additional data sources within and outside the organization are covered in-depth. Besides, the learners will explore advanced Excel functionalities to data analysis and employ various techniques like summarization, sorting, filtering, and pivot tables throughout this program. 

Finally, the learners will understand the practical aspects of creating stunning visualization to communicate analysis results in an interactive way which is essential in an organization. 

The course curriculum includes:

Introduction to Data Analytics

The first module presents a gentle introduction to the concepts of data analysis, the role of data analysts, and various tools to perform the tasks in a business environment. In addition, the learners will gain knowledge about the data ecosystem and the fundamentals such as data collection and data mining. Furthermore, soft skills such as communicating results of the analysis to stakeholders. Furthermore, the learners will have explicit knowledge about the roles of a data scientist, data analyst, and data engineer. Besides, the concepts on big data platforms, tools for on-premise and cloud, data warehouse are covered throughout this module.

Excel Basics for Data Analysis

In this module, the working knowledge is focused upon various concepts on using Excel spreadsheets for data analysis. There are multiple demos and follow-along examples to build the practical experience of the learners. In addition, concepts like data cleansing, data wrangling, and other techniques like filtering, sorting, and pivot tables are provided. Moreover, this module followed practice and applied to learn approach, with each concept covered through hands-on exercises. The learners will understand data manipulation and organizing and formatting data to make reports readable.

Data Visualization and Dashboards with Excel and Cognos

The final module deep dives into the first steps of data visualization development with the help of spreadsheets and dashboards. The learners will learn how to add charts, pivot functions, and create dashboards with unique properties to transform the data. Besides, the learners will gain valuable experience working with the IBM Cognos Analytics tools to create interactive dashboards.

Instructor: Rav Ahuja, Sandip Saha Joy, Steve Ryan, and Kevin McFaul

Level: Beginner

Duration: 4 months

User Review: 4.8/5

No. of Reviews: 771

Price: Free Enrollment (Additional charges for certification may apply)

2. Data Mining Specialization by University of Illinois – Coursera

Data Mining Specialization by University of Illinois – Coursera

The course is offered on Coursera. This certificate program offers comprehensive knowledge about data mining techniques for structured and unstructured data, understanding data schema and natural language text, and applying tools and techniques for data analysis. 

In addition, the learners will explore concepts with practical examples on pattern discovery from data, clustering, text retrieval, text mining, data analytics functionalities, and data visualization. Although this specialization is part of the Master of Computer Science Degree in Data Science, it can be enrolled separately. 

The course modules are:

  • Data Visualization
  • Text Retrieval and Search Engines
  • Text Mining and Analytics
  • Pattern Discovery in Data Mining
  • Cluster Analysis in Data Mining
  • Data Mining Project

Instructor: John C. Hart, Jiawei Han, and ChengXiang Zhai

Level: Intermediate

Duration: 8 months

User Review: 4.5/5

No. of Reviews: 1820

Price: Free Enrollment (Additional charges for certification may apply)

3. Introduction to Data Analytics for Managers by University of Michigan – edX

The course is available on edX for enrollment for new participants. In this program, the learners will explore data science techniques and tools for analyzing business data, explore Microsoft Azure for analytics with the help of programming languages like SQL. Furthermore, the learners will delve into the machine learning concepts and statistical techniques and their application in businesses. 

There are real-world case studies explored in the course to identify how expert data analysts leverage data and their big data skill alongside other analytical techniques to improve the company’s overall performance. In addition, there are hands-on learning sessions where learners will understand the programming environment to use the tools and understand applying data science in business. 

Besides, the learners will understand the graphical development environment that allows the use of advanced tools without coding requirements and perform several data analytical tasks from scatter plots, relationship assessment, SQL queries to acquire data from multiple resources, hypothesis tests, and machine learning experiments for data analysis.

Instructor: Amitabh Sinha and Sanjeev Kumar

Level: Intermediate

Duration: 6 weeks

User Review: NA

No. of Reviews: NA

Price: Free Enrollment ($50 for Optional Upgrade and Certification)

4. Data Analytics for Business by Georgia Tech – edX

Data Analytics for Business by Georgia Tech – edX

This online program is offered on edX. The certificate course focuses on providing the essential concepts of cutting-edge technologies in the field of data analytics used in every industry. 

Some of the key concepts covered in this program include data transformation and finding insights for businesses. In addition, the learners will cover various challenges encountered in data analysis and the methodologies for improving the performance. Furthermore, from the technical perspective, the learners will deep dive into business analytics algorithms and the programming language for mastering the skills. 

At the end of the course, the learners will have comprehensive knowledge about systematically approaching business problems using data analytics to improve business performance and develop new analytical ideas for analyzing data using various business analytics software and programming languages.

Instructor: Frederic Bien

Level: Beginner/Intermediate

Duration: 16 weeks

User Review: NA

No. of Reviews: NA

Price: Free Enrollment ($840 for Optional Upgrade and Certification)

5. Become a Data Analyst Nanodegree Program – Udacity

This nanodegree program is offered on Udacity. In this course, the learners will advance their programming skills to work on complex datasets and business problems. Additionally, the concepts of preparing data and creating visualizations for data exploration will be covered in-depth with various hands-on sessions. 

Finally, the learners will learn to implement Python, SQL, and statistics to uncover critical findings from enormous datasets and communicate data-driven business solutions to the management. There are few prerequisites for the course that includes prior experience working with data using Python and knowledge about the Python libraries.

Moreover, the learners must complete the final capstone project to attain the data analyst career certificate. Besides, the course provides technical mentorship and project feedback from experienced industry leaders. 

The course curriculum includes:

  • Introduction to Data Analysis
  • Practical Statistics
  • Data Wrangling

Instructor: John Bernhard, Sebastian Thrun, Derek Steer, Juno Lee, Mike Yi, David Venturi, and Sam Nelson

Level: Intermediate

Duration: 4 months

User Review: 4.6/5

No. of Reviews: 2250

Price: $310/Month/$1056 for 4-Month Access

6. Data Analysis with Pandas and Python – Udemy

Data Analysis with Pandas and Python – Udemy

The data analysis tutorial is offered on Udemy. The learner will explore data analysis techniques using the Python programming language and the associated libraries in this course. Moreover, the concepts on performing data operations such as grouping, pivoting, and joining data are covered with practical sessions to build the programming skills of the learners. 

Data manipulation and resolving broken or incomplete datasets are critical topics covered throughout the practical exercises. The perquisites include the basic experience of Microsoft Excel or other spreadsheet software, Python programming basics, and advanced knowledge of data types. 

The course modules are:

  • Installation and Setup
  • Python Crash Course
  • Series and Data Frames
  • Filtering Data
  • Data Extraction
  • Working with Text Data
  • MultiIndex
  • The GroupBy Object
  • Merging, Joining, and Concatenating Data Frames
  • Working with Dates and Times in Datasets
  • Input and Output in Pandas
  • Visualization
  • Options and Settings in Pandas
  • Conclusion

Instructor: Boris Paskhaver

Level: Beginner/Intermediate

Duration: 20 hours and 37 minutes

User Review: 4.6/5

No. of Reviews: 14,674

Price: $17

7. Data Analyst Master’s Program in Collaboration with IBM – Simplilearn

Data Analyst Master’s Program in Collaboration with IBM – Simplilearn

This is a specialization program available on Simplilearn. The certification program is well-equipped with foundational concepts to the advanced concepts for learners to become experts in data analysis. 

The learners will explore the tools and techniques for data analytics and gain the expertise of working with SQL databases and the programming languages such as Python and R. Furthermore, the learners will learn to create data visualizations and apply statistical techniques to perform predictive analysis for a business environment. 

By the end of the course, the learners will enhance their programming skills and the tools to perform essential tasks such as descriptive and inferential statistics, hypothesis testing, Tableau for data visualization, Power BI and organizing data using dashboards. 

The course curriculum includes:

  • Introduction to Data Analytics
  • Business Analytics with Excel
  • Tableau Training
  • Programming Basics and Data Analytics in Python
  • Data Science with R Programming
  • Math Refresher
  • Statistics Essential for Data Science
  • Electives: Power BI, Programming Refresher, Industry Master Class Data Analytics, SQL Training
  • Data Analyst Capstone

Instructor: Industry Professionals

Level: Beginner/Intermediate

Duration: Self-Paced

User Review: 4.6/5

No. of Reviews: 37,546

Price: $610

8. Post Graduate Program in Data Analytics by Purdue University – Simplilearn

The post-graduate program is offered in collaboration with IBM. It is available on Simplilearn. In this course, the learners will cover critical topics in data analysis such as data visualization, regression techniques, and supervised learning with various applied learning models to gain practical experience with industry projects. 

Additionally, the learners will cover statistical concepts and perform data analysis using programming languages like Python, and R. Besides, interacting with databases using SQL and visualizing data using Tableau and Power BI will be covered thoroughly through various follow-along demonstrations and practical assignments. Three capstone industry projects are mandatory to be completed successfully to be eligible for the certification. 

The course curriculum includes:

  • Analytics Foundation
  • Programming foundation and Data Analytics with Python
  • R Programming for Data Science
  • Tableau Training
  • Electives: Power BI, Introduction to Artificial Intelligence Course, Master Class- Purdue University, Industry Master Class- Data Analytics
  • Data Analyst Capstone

Instructor: Patrick J. Wolfe and Ronald Van Loon, Purdue University Experts and IBM Experts

Level: Beginner/Intermediate

Duration: 8 months

User Review: 4.6/5

No. of Reviews: NA

Price: Monthly: $76.7/One-Time Fee: $2312

9. Data Analytics with R Certification Training – Edureka

The course is available on Edureka. This certification training will help learners to gain expertise in R programming. Besides, the learners will have a solid understanding of the concepts of data manipulation, exploratory data analysis, data visualization, data mining, regression, and sentiment analysis. 

Additionally, the learners will work on various real-world case studies across retail and social media domains. 

Finally, advanced topics such as the ensemble of decision trees and collaborative filtering are covered with follow-along examples. 

The takeaways from the course are:

  • Thorough understanding of the concepts around business intelligence and business analytics.
  • Recommendation systems, association rule mining, user-based collaborative filtering.
  • Item-based collaborative filtering
  • Supervised learning techniques
  • ANOVA
  • Algorithms like decision trees, logistic regression, support vector machines, and ensemble techniques
  • R packages for plots
  • Additional machine learning techniques for data analysis

The course curriculum includes:

  • Introduction to Data Analytics
  • Introduction to R Programming
  • Data Manipulation in R
  • Data Import Techniques in R
  • Exploratory Data Analysis
  • Data Visualization in R
  • Data Mining: Clustering Techniques
  • Association Rule Mining and Collaborative Filtering
  • ANOVA and Sentiment Analysis
  • Decision Tree and Random Forest
  • Project Work

Instructor: Industry Professionals

Level: Intermediate

Duration: 5 weeks

User Review: 5/5

No. of Reviews: 25,000

Price: $245

10. Data Analysis for Decision-Making by Rochester Institute of Technology – edX

Data Analysis for Decision-Making by Rochester Institute of Technology – edX

This training program is available on edX. The course is focused on preparing participants to work with data efficiently and transform the data into information. There are in-depth concepts on data visualization, big data, data collection, and various analytical tools for data analysis. Additionally, the learners will be able to gain proficiency with software and programming languages to read, write, interpret, and communicate data, including the understanding of data sources and constructs. 

At the end of the course, the learners will be well-equipped with handling data, using Microsoft Excel to organize and clean data, creating data analysis plan, Tableau for graphical and tabular representations and visualizing data, and integrating various points of the data with other information to derive business information for decision-making. 

Finally, the learners will also have the skillset to identify any misrepresentations of data and accurately transform them for representations. 

The course modules include:

  • Data Literacy Foundations
  • Data Processing and Analysis with Excel
  • Data Representation and Visualization in Tableau

 Instructor: Beth Prince-Bradbury

Level: Beginner/Intermediate

Duration: 3 months

User Review: NA

No. of Reviews: NA

Price: Free Enrollment ($761 for Optional Upgrade and Certification)

11. Become a Data Analyst Learning Path – LinkedIn Learning

Become a Data Analyst Learning Path – LinkedIn Learning

The learning path comprises various courses from the beginner to the advanced concepts to master data analysis skills. It is available on the LinkedIn Learning platform.

In this course, the learners can expect to cover concepts on examining data, various tools for data analysis, and the basics of mathematical and statistical skills required to be a successful data scientist. Besides, the learners will communicate the information acquired from the analysis and the concepts of data visualization and its importance.

Throughout the program, the learners will be working on their problem-solving skills with practical sessions to gain expertise. 

The course curriculum includes:

  • Learning Data Analytics
  • Data Fluency: Exploring and Describing Data
  • Excel Statistics Essential Training
  • Learning Excel: Data Analysis
  • Learning Data Visualization
  • Power BI Essential Training
  • Tableau Essential Training

Instructor: Robin Hunt, Barton Poulson, Joseph Schmuller, Curt Frye, Bill Shander, and Gini von Courter

Level: Beginner

Duration:24 hours

User Review: NA

No. of Reviews: NA

Price: Prices available on Sign-Up

12. Data Analytics Using Python Expert Track – FutureLearn

Data Analytics Using Python Expert Track – FutureLearn

The expert track is a specialization course offered on Futurelearn. This program is co-created by Futurelearn, Coventry University, in collaboration with GitHub. The training program includes fundamentals and advanced concepts of Python programming necessary for performing advanced analytics on complex business problems. Furthermore, the learners will explore how to work quickly with data using tools and libraries and integrate systems effectively. Besides, the learners will understand the entire procedure from data collection, manipulation, and organizing data to conclude decision-making. 

In addition, the learners will gain proficiency in dealing with large datasets using various tools and techniques for analysis. Next, the learners will delve into advanced concepts of exploring data using Python and how to develop critical elements of Python for demonstrating data. 

The concepts of data ingestion using Python and understanding data types and their sources are covered in detail. The takeaways from this course include Python programming know-how, advanced data analytics, data wrangling, descriptive statistics, data query language, and fundamentals of statistical techniques. 

The course modules are:

  • Data Analytics and Python Fundamentals
  • Python Packages: NumPy and Pandas Dataframe
  • Data Wrangling and Ingestion using Python

Instructor: Ed Marks

Level: Beginner/Intermediate

Duration: 12 weeks

User Review: NA

No. of Reviews: NA

Price: $39/month

13. Data Analytics Masters Program – Edureka

This is an extensive specialization program offered by Edureka. In this online course, the learners can expect to gain proficiency with tools and systems implemented for data analytics by professionals in the industry. In addition, the learners will be provided with in-depth training for statistics, R programming, and Tableau. Thus, it is ideal for learners willing to work from scratch on the most advanced topics. Some of the essential topics covered in the course are:

  • Exploratory analysis
  • Statistics fundamentals
  • Data visualization
  • Probability
  • Advanced SAS procedures
  • Tableau
  • Bayesian inference
  • Regression modeling
  • Data manipulation
  • Data mining
  • Sentiment analysis
  • Advanced statistical techniques
  • SAS Macros
  • PROC SQL
  • SAS ODS
  • LOD Expressions
  • Tableau
  • Data visualization
  • Integration with R

The course modules are:

  • Statistics Essentials for Analytics
  • Data Analytics with R Training
  • Tableau Certification Training Course
  • Microsoft Power BI Certification Training Course
  • AWS S3
  • Data Analyst Master Capstone Project

Instructor: Industry Professionals

Level: Beginner/Intermediate

Duration: 24 weeks

User Review: NA

No. of Reviews: NA

Price: $1800

Conclusion

The data analytics career is exciting with excellent opportunities due to the increasing demand to fill the vacant positions of expert job roles. Today, organizations seek professionals like data scientists, data analysts, or data engineers to churn massive datasets to provide intelligent business analysis and gain competitive advantages through data-driven insights. With high-paying jobs, opportunities are in abundance for those looking to begin a career in the field of data analytics. 

Whether aspirants or professionals looking for a mid-career, switching into this field requires upskilling themselves with the latest technologies and tools to prosper as a top data analyst. As per Glassdoor reports, a data analyst earns an average of $70,000, which varies according to location, skills, and experience.

The estimated salary of the most experienced individual is stated as $110,000, which is by far one of the best paying jobs in the industry. Although there are data analysts with various backgrounds, it is essential to understand the visualization tools, the programming proficiency and to understand various types of data and its sources, including the advanced concepts and technologies. 

With new technologies like machine learning and big data entering the data analytics space, the competition for top positions has toughened. Therefore, those aiming for a career in data analytics must opt for courses that provide tremendous value for money, alongside theoretical and practical content and an industry-recognized certificate. 

This article highlighted some of the top trending and highly rated courses to enhance career prospects and climb the hierarchical ladder of success with lucrative offers, salary, and growth.

Introduction

In today’s date and age, accessing learning material and gaining new job skills is easy to do. There are all kinds of learning solutions available online, with more colleges and universities than ever beginning to offer alternative learning paths for motivated (yet remotely-located) students. 

You don’t have to enroll full-time at a college or university in order to access these opportunities, either. In fact, there are plenty of online learning platforms that you can look into to take courses in relevant skills and subjects no matter where you live-  or how much money you have. From Coursera to Udemy, you’ll find plenty of online learning courses to help you meet your professional and personal goals.

One of these online learning platforms is the LinkedIn Learning platform. In this LinkedIn Learning review, we will tell you everything you need to know about this unique online course provider.

 

What is LinkedIn Learning?

LinkedIn Learning is one of the country’s top providers of online learning solutions and professional development opportunities. Whether you’re an individual hoping to pick up a few skills here or there or an organization looking to expand your employees’ access to professional development opportunities and new skills, LinkedIn Learning has the resources you need for today – and for tomorrow.

The platform features more than 16,000 courses taught by experts with real-world experience. You’ll find more than 50 brand-new classes offered each and every week with more classes constantly being added. The course library is, in fact, kept up to date with the most in-demand skills and content that you need to know.

Sign up for a LinkedIn Learning subscription, and you’ll join a network of more than 600 million follow members. You’ll receive personalized recommendations for courses that will help to connect you with the most relevant online learning solutions and resources for your needs and goals.

 

How Does LinkedIn Learning Work?

LinkedIn Learning offers students three primary ways to learn.

You can learn by subject, which will enable you to gain experience in a specific skill set. You can select a topic and pick classes that revolve around that area of interest.

You can also gain skills in software, which is vital for all kinds of industries. You can even pursue a Learning Path, which is a feature that is unique to LinkedIn Learning. 

With Learning Paths, you’ll gain the skills necessary to transition into a new field. You can select a path and gain access to a structured learning experience based on that path, rather than having to wade through the thousands of courses listed on the platform. 

An example? If you want to learn new skills in digital marketing, for example, you’ll start by taking a class in online marketing foundations before moving on to those in Google Analytics, growth hacking, content marketing foundations, and other related and more advanced topics.

 

Features and Functionality

There are several key features of LinkedIn Learning that set it apart from other platforms. Here are some of the best.

 LinkedIn Learning Course Features

Ease of Access & Functionality

Already have a LinkedIn account? That’s great! You won’t have to do a single thing when it comes to filling out your profile and registering for LinkedIn learning. You’ll just have to register and pay the fees, if you progress past the free trial. After that, you can access all LinkedIn Learning features that you might want. You’ll find that everything is formatted quite similarly to the regular LinkedIn platform, too.

 

Course and Video Features

LinkedIn Learning has several courses and video features that are incredibly beneficial for all subscribers. 

One is the certificate of completion feature. Every course, regardless of the category or your own skill level, comes with a certificate of completion at the end. This is a great way to showcase to prospective employers that you really know your stuff.

You’ll also be able to access things like exercise files, notes, and assessments. Exercise files are perfect for helping you gain mastery of a subject, as you’ll be able to practice the skills taught in the class in a more hands-on way. Notes are beneficial because you can take digital notes as you move along in a course so that you can reference them later on.

Assessments are beneficial because you can take these at the end of each individual section in the course. You’ll know exactly when it’s time to move on to a new module based on what you’ve accomplished so far. 

You’ll also have access to learning paths and saved courses. Learning paths are unique to LinkedIn Learning and will allow you to take classes in a certain progression if you want to gain mastery of a certain larger topic. You can also save courses and return to them later on so that you don’t lose track of what you wanted to do.

If you’re looking to read a few LinkedIn Learning honest reviews, then don’t worry – you’ll also be able to access helpful review sections where you can read feedback given from other students. This is particularly beneficial in helping you to decide whether a course will mesh well with your unique learning goals.

Similarly, LinkedIn Learning has a helpful Q&A section where you can ask questions of fellow students and the instructor. This is a great way to learn more about a topic or to clear up any areas of confusion that you might have.

 

Support Services

There are all kinds of ways you can get help if you find that you are having trouble with LinkedIn Learning.

The best place to start is with the Learning Help Center, which will include answers to some of the most commonly asked questions. You can also reach out to support by signing in or creating a help ticket, too.

 

Learner History

LinkedIn Learning offers students a great way to keep track of their professional growth. With the learner history feature, you’ll be able to access a list of the courses you have watched in the past. The beauty of this system is that, if you are an individual LinkedIn Learning subscriber migrating from the original platform, Lynda.com, all of your data can be transferred to LinkedIn Learning.

Not only that, but you can search, view, save, and share courses with the platform, too. This is a fun way for you to keep in touch with your professional network both on and off the platform. LinkedIn Learning will even provide you with recommendations of skills you might be interested in and other recommendations, too.

 

What Type of Classes are Offered on LinkedIn Learning?

With LinkedIn Learning, you can take classes in just about anything. From project management to JavaScript, HTML to body language, LinkedIn Learning is the place to go. 

For the most part, courses are offered in three categories – business, technology, and creative pursuits. In the business category, you might take classes in things like leadership development or soft skills training. In technology, you may build your skills in hardware or software programming. And in the creative category, you’ll likely gain the skills necessary to help you become more adept with design and other skills.

 

 

How to Choose Courses

To get started with LinkedIn Learning, you will need to first register for an account. This is the same registration process that you would follow if you were making an account for a general LinkedIn profile as well, so you might already be familiar with the process 

Once you have created an account, you will be able to select from a general list of skills of those that interest you most. For example, you might select options like “writing,” “marketing,” “public relations,” or “Microsoft Office.”

After you have selected your skills, the platform will give you a list of course recommendations that correlate with the interests and skills you’ve indicated.

If you’d rather be more autonomous in the selection of your classes, you do have another option. You can discover courses based on browsing through various fields. LinkedIn Learning has three basic categories – creative, business, and technology. You can also look at classes that are trending as well as those that are listed as “top liked” to give you an idea of what kinds of courses other students are taking.

You can even search directly if you know exactly what you want to get out of the platform. There’s a convenient search tool that will enable you to search by the exact name of the course.

 

What’s the Price/Cost of LinkedIn Learning?

LinkedIn Learning Pricing

LinkedIn Learning, like most other online course platforms, has several different pricing structures for you to consider.

As with similar platforms, you can sign up for a free trial to get started. This will help you get an idea of whether the platform is one you’d like to pursue, or whether you’d prefer to move to a different online learning platform to complete your courses.

Although LinkedIn Learning is not the cheapest platform you’ll find, it’s definitely not the most expensive – nor does it even remotely come close to the price of registering for a class at a college or university.

At $29.99 per month, the cost of a LinkedIn membership is relatively affordable, particularly if you plan on taking multiple classes every month. In addition to a monthly rate (which is free the first month with the trial program), LinkedIn Learning also features an annual rate that allows you to save the cost of a subscription. With this plan, you’ll pay $19.99 per month, but you must pay all at once for the entire year.

You can cancel at any time if you decide to move to another platform, or if you merely decide that online learning is not right for you.

 

The Advantages (Pros) of LinkedIn Learning

 

Integrated with LinkedIn Accounts

If you already have a LinkedIn account, you’ll love using LinkedIn Learning because everything is set up and designed in a similar fashion. The platform has access to your job profile, skills, areas of expertise, and subjects of interest, so you’ll find that courses are automatically recommended based on this profile. You’ll have to do less work when it comes to finding relevant courses.

 

Free Trial Available

One of the best features of LinkedIn Learning is the availability of a free trial program. This is the absolute best way for you to get an idea of whether a course or course platform is right for you before you commit. You don’t have to pay a cent if you decide, after the first month, that LinkedIn Learning isn’t right for you.

 

Accessible and Relevant Courses

With LinkedIn Learning, you’ll have access to more than 10,000 different expert-led courses. These courses are integrative and hands-on and can be completed from any device, including a phone or a computer. In most cases, you can even download your courses so that you can view and complete them offline, while you’re on the go.

In addition to personalized course recommendations from the platform, you will also be able to assess your progress with quizzes while you complete each individual course. Although the quizzes aren’t graded, they offer a good way for you to keep track of how well you are doing and whether you have achieved the listed course objectives. 

Beyond the quizzes, there are plenty of other resources that can be found in each course on this platform. For example, you’ll earn a certificate when you complete a course. Granted, this kind of course completion is not credit-bearing in any way, and the certificate won’t always help you in your job search. But in many cases, the certificate can be a good way for you to demonstrate to potential employers that you really know your stuff and that you have gone out of your way to learn new skills.

There are project files you can access while you learn, too. These project files are tools and activities that you can view or complete while you’re working on a course to help you truly master the content. After all, the best way to learn is by actually doing!

You will also be able to access LinkedIn’s premium career features, something that can be invaluable as you are searching for a job.

 

The Disadvantages (Cons) of LinkedIn Learning

 

Short, Introductory Courses

One of the primary disadvantages of LinkedIn Learning is that courses tend to be short and targeted for beginners who are at a more introductory level. If you want to gain a more advanced knowledge of a topic, you would be better off signing up for a course offered by a university. LinkedIn Learning provides more of an overview or skim rather than a detailed experience.

 

Some Material is Not Up To Date

Some LinkedIn premium students have complained that the platform does not offer students any way to know how old a course is before deciding to take it. That might not be a problem at face value, but when you consider that some material is time-sensitive, it might make you think twice. 

For some fields, it might not make a huge difference. Chances are, if you are taking a creative writing class, there’s not much that will change from one year to the next. For skills related to technology or business, though, it might be more imperative that you take a recently-launched course.

 

Too Many Courses?

Although it might seem impossible, the reality is that, when taking classes with LinkedIn Learning, you might have too much of a good thing. LinkedIn Learning has so many classes to choose from that it can be somewhat overwhelming when it comes to choosing the right ones.

This challenge is amplified when you realize that not all courses on LinkedIn Learning are equally awesome, either. Some are taught by instructors who might not have the best teaching style – or perhaps a teaching style that doesn’t mesh with your goals and preferences – while others are taught by individuals who proclaim to (but may actually not) know much about the topic at hand.

 

Ungraded Material

A complaint frequently echoed among LinkedIn Learning subscribers is that you will not receive a grade for your work after completing various modules within a course. Although this makes sense, given that LinkedIn Learning does not provide students with grades at the end of the course or any kind of credential (like transferable course credit), it can be frustrating for some that you must pay for a membership and yet not get anything tangible at the end of the class.

 

The Learner’s Perspective

From a learner’s perspective, LinkedIn Learning has a whole lot to offer. Not only is this platform great for learning casual skills that will enrich your everyday life, but it’s also one of the best resources out there if you are searching for a job.

Although the classes you can take on LinkedIn Learning are not credit-bearing, the beauty of them is that they connect to your LinkedIn profile so they can easily be displayed there and help to snag the attention of a recruiter or hiring manager. They’ll help you supercharge your resume and show that you are motivated and want to succeed.

 

The Instructor’s Perspective

Do you think you have what it takes to teach a class on LinkedIn Learning? From soft skills to software development, there’s likely a niche for everyone.

The platform is just as beneficial to educators as it is to students, offering every LinkedIn Learning instructor a way to consolidate their material and get their wealth of knowledge out there to the public. You’ll be able to upload all kinds of materials, from PDFs to videos and links.

You can even integrate digital resources into your curriculum, something that is unique for LinkedIn Learning as compared to other platforms. There are closed captioning and other accessibility services you can tap into, too, making this platform one of the best and most all-inclusive.

LinkedIn Learning is best for experts, so if you’re new to your field, this might not be the best platform for you. As an instructor on LinkedIn Learning, you will be able to help students reach their personal and professional goals and make a little extra income. You do have to apply in order to become an instructor.  You’ll need to submit a maple movie and indicate what topics you are qualified to teach.

 

Conclusion

Hopefully, this LinkedIn Learning courses review has been helpful in helping you decide whether a LinkedIn Learning subscription is right for you. While there are certainly areas where the LinkedIn Learning app could be improved, overall, this platform is one of the very best when it comes to making online learning a reality for all students.

 

FAQ

 

Is LinkedIn Learning Worth it?

Whether you’re a serious or casual learner, LinkedIn Learning is absolutely worth the time and money you might invest in the platform. Whether you want to develop skills that you might need for a job search or just want to learn something fun, new, and exciting in your spare time, LinkedIn Learning is the way to go.

 

Is LinkedIn Learning Legit?

Is LinkedIn Learning legit? Absolutely. This platform is loaded to the brim with all kinds of educational material that is not only practical and useful, but also actionable and enjoyable to learn.

 

You will find that the materials here are relevant for both beginning and intermediate learners. Although the focus is primarily on job skills, the skills that you acquire with a LinkedIn learning membership could very well help you to become more fluent in skills that you use in your day-to-day life and hobbies, too.

 

Is LinkedIn Learning Free?

LinkedIn Learning does offer a free membership trial, but after the one month has ended, it is no longer free. You will need to pay a monthly fee between $19.99 and $29.99, depending on the length of the subscription plan you choose.

 

How Much Does LinkedIn Learning Cost?

If you sign up for a monthly Premium subscription, you will pay $29.99, renewed automatically each month. If you would prefer to pay just once per year, you will need to pay $299.88 plus relevant taxes. This is a discount of approximately 33% and will cost you around $19.99 per month.

 

What is a LinkedIn Learning Subscription?

A LinkedIn Learning subscription will entitle you to all kinds of benefits via the platform. Not only will you be able to get recommendations for courses based on your interests and decision skills, but you can also add those courses to your LinkedIn profile to showcase them to potential employers.

A LinkedIn Learning subscription goes hand in hand with other benefits. For example, you’ll not only be able to access interactive learning opportunities but you can learn how and when you want and gain full access to LinkedIn premium, where you’ll receive job and salary insights, unlimited profile viewing, InMail credits, and more.

You’ll be billed on a monthly or annual basis, depending on the option you choose. Regardless of which one you select, your subscription will be renewed at the end of every month or the end of every year. Pay annually, and you’ll save up to 33% compared to monthly costs.

You can always downgrade or cancel your subscription later on, too. Although LinkedIn does not offer refunds except in very rare situations, you can make changes to your plan at any time. Not only that, but as an employer, you can also pay for your employees’ subscriptions. After your purchase, you’ll get the receipt in your email and you can use it for filing expense reports.

 

Are LinkedIn Learning Courses Good?

LinkedIn Learning courses are good – and they’re definitely worth it. If you’re interested in spending a couple of hours each week on learning new skills or enhancing the ones you already have, it’s a solid investment that can benefit both you and your carer. As long as you are willing to do some research on your courses and your instructors, there really aren’t any drawbacks associated with the platform, either.

 

Are LinkedIn Learning Courses Recognized & Accredited?

Although most employers will view LinkedIn Learning courses as a solid badge of achievement on your resume when it comes to applying for jobs, they, unfortunately, are not accredited by any organization, nor are they formally recognized. You won’t be able to use them to transfer credits into a university or to help you get a job that requires a specific credential. However, taking LinkedIn Learning classes will enable you to get a leg up on the competition during your job search by providing you with skills that employers want to see the most.

 

Can You Put LinkedIn Learning On Your Resume?

Absolutely. In fact, that’s one of the biggest benefits of taking courses on LinkedIn Learning. When you take a LinkedIn Learning class, you’ll be able to add the course to your LinkedIn profile to showcase to prospective employers and to the rest of your LinkedIn network.

 

Introduction

Penetrating testing is a legal and structured approach used for the security evaluation of an organization. It is commonly known as Pen testing, which allows to safely assess the security posture by safely exploiting the vulnerabilities of the IT infrastructures such as operating systems, security flaws within services and applications, devices, and configurations. It helps ensure that the organizations are well-equipped with defensive mechanisms and adherence to security policies. 

Such testing is conducted manually or via automated technologies to identify the exploitable areas and help build effective strategies and prioritize remediation approaches to have a well-controlled environment that safeguards all the organizational infrastructures and the end-users of the applications or services of these organizations. 

With the rapid incidence of cyber-attacks, penetration testers are among the highest paid professionals in the IT industry, with an expected growth rate of 31 percent as per the US Bureau of Labor Statistics. As per the reports, penetration tester employment is projected to be growing much faster than the average of most job roles in the IT industry. Thus, aspirants need to gain expertise about penetration testing skills from top-tier universities and organizations through various online courses and deep dive into an exciting and future-proof career of immense growth potential.

Related reading: 10 Best Online Cybersecurity Courses

1. Penetration Testing, Incident Response and Forensics by IBM – Coursera

Penetration Testing, Incident Response and Forensics by IBM – Coursera

This course is available on Coursera. In this training program, the learners will provide the necessary background to gain cybersecurity skills and understand various phases of pen-testing. Furthermore, the learners will explore the concepts of gathering data for the testing and the popular testing tools that are available today. In addition, the topics on incident response, documentations to collect, and the components of incident response policy are covered in-depth.

There is also a provision of hands-on sessions for learning scripting for system analysis. By the end of the course, the learners will be well-equipped to know penetration testing tools, incident response tools and techniques, digital forensics, and digital evidence and scripting languages. 

The course curriculum includes:

  • Penetration Testing
  • Incident Response
  • Digital Forensics
  • Introduction to Scripting

Instructor: IBM Global Subject Matter Experts

Level: Beginner

Duration: 17 hours

User Review: 4.6/5

No. of Reviews: 863

Price: Free Enrollment (Additional charges for certification may apply)

2. Cybersecurity Fundamentals by New York University – edX

This certification program is a Micro Bachelors specialization offered on the edX platform. In this course, the learners can cover core cybersecurity components such as information security, network security, and penetration testing.

Furthermore, the learners will be exposed to Python scripting for system analysis and gain hands-on experience with various tools that professionals use and defense mechanisms organizations employ. 

In addition, the concepts on various complexities in defending business systems, cyber threats, risk assessment, intrusion detection, and vulnerability management are some of the advanced topics covered in-depth. The learning content and materials provided in the course also help prepare for the CompTIA’s Security+ Certification exam. 

The key takeaways from the course are:

  • Ethical security mindset.
  • Implementing various security design principles.
  • Access control and reference monitors.
  • Applying security policies in operating systems.
  • Basic analysis for secured systems.
  • Virtualization and the impact on security and efficiency.
  • Implementing methodologies for penetration testing.
  • Identifying vulnerabilities, score their risk, and explain mitigations.
  • Responsible disclosure findings in a professional report can recreate the exploit, explain the impact to the target, and prioritize each finding.
  • Enumerate target hosts, domains, exposures, and attack surface.
  • Identify flaws and vulnerabilities in applications, websites, networks, systems, protocols, and configurations using manual techniques and assistive tools.
  • Reverse engineering compiled applications to discover exploitable weaknesses.
  • Writing new exploits to test various vulnerabilities on clients, against servers, and to escalate privileges.
  • Demonstrate the fundamentals of secure network design.
  • Understand the issues involved with providing secure networks.
  • Cryptography analysis is required for secure communications, authorization, and authorization.
  • Securing networks.
  • The course curriculum includes:
  • Information Security: Authentication and Access Control
  • Information Security Advanced Topics
  • Introduction to Network Security
  • Network Security Protocols
  • Network Security Advanced Topics
  • Penetration Testing: Discovering Vulnerabilities
  • Penetration Testing: Exploitation
  • Penetration Testing: Post Exploitation

Instructor: Justin Cappos and Aspen Olmsted

Level: Beginner/ Intermediate

Duration: 1 year

User Review: NA

No. of Reviews: NA

Price: $1506.7

3. Ethical Hacker Nanodegree Program – Udacity

The online learning program is offered on Udacity. The course covers a wide range of topics on ethical hacking systems and how to find the vulnerabilities and weaknesses in various applications and services, and systems. In addition, the learners will understand the design and execution of a penetration testing plan and report the pen test findings with valid evidence. 

The learners will also gain the programming skills required to conduct software testing and learn scripting languages to perform the tests efficiently. There are prerequisites for the course that requires a basic understanding of Linux file structure and commands, networking basics, working knowledge of any programming knowledge, familiarity with operating systems, and basics of encryption. 

The course curriculum includes:

  • Introduction to Ethical Hacking
  • Penetration Testing and Red Teaming Operations

Instructor: Sagar Bansal and Paul Oyelakin

Level: Advanced

Duration: 2 months

User Review: NA

No. of Reviews: NA

Price: $310/Month/$528 for 2-Month Access

4. Website Hacking, Penetration Testing, and Bug Bounty Hunting – Udemy

Website Hacking, Penetration Testing, and Bug Bounty Hunting – Udemy

This is a comprehensive course on website penetration testing. It is available on Udemy. The learners will explore web application hacking concepts and discover bugs such as black-hat hackers and more. 

The training follows a practical approach and provides sufficient exposure to testing tools and techniques, different security components in websites, and understanding how to discover, exploit and mitigate common security vulnerabilities under web application testing.

Additionally, the learners will cover advanced topics such as bypassing security, escalating privileges, accessing databases, and server-related information for pen tests. The participants will master a wide range of topics such as:

The course curriculum includes:

  • Introduction
  • Creating a Penetration Testing Lab
  • Linux
  • Website Basics
  • Information Gathering
  • File Upload Vulnerabilities
  • Code Execution Vulnerabilities
  • Local file Inclusion and Remove File Inclusion
  • Remote File Inclusion
  • SQL Injection Vulnerabilities: SQLi Login pages, Extracting Data from Database, Advanced Exploitation
  • XSS Vulnerabilities
  • Insecure Session Management
  • Brute Force and Directory Attacks
  • Automatic Discovery of Vulnerabilities
  • Post Exploitation

Instructor: Zaid Sabih and Z Security

Level: Beginner/Intermediate

Duration: 10 hours 4 minutes

User Review: 4.6/5

No. of Reviews: 12,494

Price: $69.6

5. Ethical Hacking: An Introduction by Coventry University – FutureLearn

This course is offered by Coventry University in collaboration with the Institute of Coding. It is offered on the Futurelearn platform. The course begins with the introductory concepts on ethical hacking, legal aspects of penetration testing, penetration testing methodologies, and practical sessions for hacking exercises. Besides, the learners will deep dive into standard penetration testing approaches and perform simple vulnerability attacks on a targeted system. The prerequisites include basic knowledge of computer science.

Instructor: Daniel Goldsmith, Christo Panchev, and Antal Goldschmidt

Level: Beginner

Duration: 2 weeks

User Review: 4.4/5

No. of Reviews: 34

Price: Free Enrollment with upgraded Access: $74, and unlimited Access: $279.9/yr

6. Cybersecurity Basics IBM – edX

Cybersecurity Basics IBM – edX

The online program is available on edX. This training program builds a solid foundation of the basics of cybersecurity. From cybersecurity history to exploring various cybersecurity threats are covered in detail. Moreover, the course provides essential concepts on the tools that are required to prevent an attack.

In addition, the learners will delve into penetration testing concepts in cybersecurity and the role of cryptography and its uses. In addition, the learners will cover the functions and types of firewalls, and different types of cybersecurity attack models, including the primary components of confidentiality, integrity, and availability.

The course contents are:

  • History of Cybersecurity
  • A Brief Overview of Types of Actors and Their Motives
  • Key Security Concepts
  • An Overview of Key Security Tools and Penetration Testing

Instructor: Coreen Ryskamp

Level: Beginner

Duration: 4 weeks

User Review: NA

No. of Reviews: NA

Price: Free Enrollment ($150 for an optional upgrade for certification)

7. Certified Ethical Hacking Course by EC Council – Simplilearn

This certification course is offered on Simplilearn and is accredited by EC Council. In this program, the learners will cover the advanced processes in Ethical hacking, advanced penetration testing concepts for network security, and system penetration techniques.

There are numerous hands-on training sessions, and the course contents strictly follow the latest contents that are in line with the industry-recognized certificate exam by EC Council for a cybersecurity career.

Additionally, the learners will cover the topics of Trojan backdoors and countermeasures, IDS firewalls and honeypots, advanced hacking techniques and concepts, network packet analysis, mobile and web technology testing, and advanced log management.

The course contents are:

  • Introduction to Ethical Hacking
  • Footprinting and Reconnaissance
  • Scanning Networks
  • Enumeration
  • Vulnerability Analysis
  • System Hacking
  • Malware Threats
  • Sniffing
  • Social Engineering
  • Denial-of-Service
  • Session Hijacking
  • Evading IDS, Firewalls, and Honeypots
  • Hacking Web Servers
  • Hacking Web Applications
  • SQL Injection
  • Hacking Wireless Networks
  • Hacking Mobile Platforms
  • IoT Hacking
  • Cloud Computing
  • Cryptography

Instructor: Dean Pompilio and Bipin Kulkarni

Level: Advanced

Duration: 90 days online Access

User Review: 4.6/5

No. of Reviews: 2661

Price: $544

8. Become a CompTIA Certified Penetration Tester – LinkedIn Learning

Become a CompTIA Certified Penetration Tester – LinkedIn Learning

CompTIA PenTest is one of the most widely recognized exams that highlights professionals’ testing and vulnerability assessment skills and is highly regarded in the industry. This learning path is available on LinkedIn Learning that includes various courses from the essentials to the advanced concepts. The topics covered in the entire program include best practices, recommended strategies, testing environment, device testing, and cloud-based testing. In addition, the learners will have sufficient exposure to the concepts that can help them clear the CompTIA exam successfully. 

The course contents are:

  • Planning and Scoping
  • Survey the Target
  • Select your Attacks I and II
  • Selecting the Pen Testing Tools
  • Using Scripting in Pen Testing
  • Reporting and Communication

Instructor: Michael Solomon

Level: Beginner/Intermediate

Duration: 11 hours

User Review: NA

No. of Reviews: NA

Price: 1-Month Free Trial (Charges may apply after trial. Prices available on Sign-Up)

9. Web Application Penetration Testing Fundamentals – Pluralsight

The course is available on Pluralsight. This tutorial builds the foundational skills of the learners with concepts on web applications, their frameworks, and how to perform a successful web application penetration test. The learners will begin from the pre-engagement of the test to prepare the tests. Next, the techniques for pen testing various web applications and web servers are covered with hands-on sessions. 

Finally, the learners will discover the types of attacks on applications, user inputs, logic flaws in the development of applications and have a solid understanding of the basic framework for web application security assessment. 

The course contents are:

  • The Principles of a Web Application Penetration Test
  • Pre-Engagement and Footprinting
  • Attacking User Controls
  • Attacking Application Inputs
  • Common Attack Methods
  • Discovering Logic Flaws
  • Reporting
  • Summary

Instructor: Mike Woolard

Level: Intermediate

Duration:2 hours 37 minutes

User Review: 4.6/5

No. of Reviews: 58

Price: 10-Day Free Trial (Charges may apply after trial. Prices available on Sign-Up)

10. Cyber Security Certification Training Course – Edureka

This course is offered on the Edureka platform. The online training comprises multiple cybersecurity concepts such as ethical hacking, cryptography, penetration testing, computer networks and security, application security, vulnerability analysis, malware threats, sniffing, SQL injection, and many more. 

The learners will begin from scratch with the fundamentals of cybersecurity and build hands-on experience across modules. Besides, the learners will understand the best practices, the technologies to protect networks, and the tools and techniques for preventing attacks and safeguarding data from unauthorized attacks. 

Finally, the learners will cover all the advanced concepts on securing applications, access management, session hijacking, and the methods to tackle these challenges in an organizational environment. 

The key takeaways from this course are:

  • Comprehensive understanding of cybersecurity
  • Security architecture
  • Security governance
  • Security Auditing
  • Regulations and frameworks
  • Ethical hacking
  • Types of hackers
  • Phases of ethical hacking
  • Penetration testing
  • Types of penetration testing
  • Footprinting
  • Types of footprinting and footprinting techniques

Instructor: Industry Professionals

Level: Intermediate

Duration: 4 weeks

User Review: 5/5

No. of Reviews: 33,000

Price: $204

11. Cybersecurity Specialization by University of Maryland – Coursera

Cybersecurity Specialization by University of Maryland – Coursera

This certificate course is offered on Coursera. In this specialization, the learners will cover the fundamentals concepts of securing systems, the hardware and software requirements, cryptography for secure interactions, and penetration testing to identify vulnerabilities. Furthermore, the learners will explore the concepts of modern best practices and build essential practical skills with the relevant tools and techniques to build better security-oriented systems. The course curriculum includes:

Usable Security

This module focuses on the design aspects of building a secure system. In addition, the basic principles of human-computer interactions as insights for building secure systems are covered in-depth. Finally, the learners will understand the goal of developing security measures within a system.

Software Security

In this module, the learners will explore the foundations of software security, software vulnerabilities, SQL injection, and session hijacking concepts. In addition, the learners will deep dive into advanced penetration testing concepts and analysis techniques that can help mitigate or prevent the attacks. Finally, the learners will cover the programming aspects of this course and work on various hands-on sessions to use techniques and at each developmental phase of building secure software systems.

Cryptography

The third module focuses on the foundations of modern cryptography and its implementation in practical applications.

Hardware Security

In this module, the learners will learn the security requirements from a hardware perspective. The learners will explore the vulnerabilities in the current digital system and understand the design flow and the form of physical attacks on the systems.

Cybersecurity Capstone Project

The final module includes the capstone project, which is mandatory to be completed successfully to attain the certificate of completion.

Instructor: Jennifer Goldbeck, Jonathan Katz, Michael Hicks, and Gang Qu

Level: Intermediate

Duration: 8 months

User Review: 4.5/5

No. of Reviews: 3795

Price: Free Enrollment (Additional charges for certification may apply)

12. IBM Security Analyst Fundamentals Specialization – Coursera

IBM Security Analyst Fundamentals Specialization – Coursera

This specialization program is available on Coursera. Throughout this course, the learners will explore digital forensics, penetration testing, and incident response concepts. Furthermore, the learners will understand threat intelligence and learn to use the tools to gather data to prevent cyber attacks in an organizational environment.

Additionally, the learners will cover the most significant breach cases and their reviews to understand from different perspectives about various threats and build their experience on incidence reporting on a real-world breach.

Finally, the learners will master the cybersecurity analyst tools to provide data and endpoint protection alongside system and network security and SIEM concepts. Besides, to enhance the hands-on experience, the learners will also learn to work with various industry-specific open source security tools. The course contents are:

Penetration Testing and Incidence Response

This module offers the learners a solid background in penetration testing and how to collect data for the tests. In addition, the learners will focus on the popular penetration testing tools and understand the various phases of incident response and various response policies and their components for risk mitigation and prevention.

Digital Forensics

The forensic process and analysis of data, including the scripting languages used for system analysis, are covered in –depth. Moreover, various techniques and tools required to identify digital evidence to prevent future attacks are covered with the help of practical examples.

Cyber Threat Intelligence

This module provides an understanding of the network defensive tactics, network access control, and network monitoring tools for threat intelligence. In addition, the learners will explore the data protection risk alongside the mobile endpoint protection requirements.

Finally, various concepts on scanning technologies, application security vulnerabilities, and threat intelligence platforms are covered comprehensively. Besides, the learners will deep dive into advanced concepts such as data loss prevention tools and data classification in a database environment, recognizing application security threats, and exploring SIEM products alongside reviewing suspicious alerts.

Cybersecurity Capstone: Breach Response

The final module includes the capstone project based on all the essential concepts covered throughout the course. The project requires learners to include incident response methodologies in a security model and categorize the critical vulnerability types. There is an additional provision of concepts on the cost of data breaches and the research studies associated with them.

At the end of the course, the learners will have complete knowledge about incident response methodologies, describing a watering hole attack, tackling ransomware threats, and third-party breaches. In addition, the learners will gain the competency to understand and take appropriate actions for point of sale attacks and performing case studies on current cyber attacks and breaches.

Instructor: IBM Global Subject Matter Experts

Level: Beginner

Duration: 4 months

User Review: 4.8/5

No. of Reviews: 404

Price: Free Enrollment (Additional charges for certification may apply)

Conclusion

Penetration testers or pen testers are the assets in any organization today. A recent IBM report suggests that the average cost of a data breach in 2021 rose from 3.86 million to $4.24 million, which is the highest average in total cost ever recorded in the 17-year history of the report. They are responsible for performing simulated tests by conducting cyberattacks on a computer system, networks, and applications to identify vulnerabilities that malicious attackers can exploit.

Although some of the pen tester jobs begin with entry-level positions in the cybersecurity field, there are endless opportunities in this domain, and they are among the most highly paid professionals in the industry. According to Indeed.com, the average salary of a pen tester in the USA is $111,737, and they are offered the highest package of $144,946 as per the region and experience of the professionals.

Nevertheless, pen testers remain the key contributors to making an organization secure in terms of applications, systems, networks, cloud environment, and more. Therefore, this job profile continues to observe a high demand and a high growth rate in the past few years. Thus, it is essential for aspirants and experienced professionals aiming to switch their career domains must opt for some of the top online courses that provide a balance of theoretical concepts and build the practical experience of the learners.

In addition, it is vital to attain the courses from some of the top-tier institutions that offer industry-recognized certificates that can provide immense value to the hiring organizations. Therefore, this article highlighted some of the top courses for penetration testing that can improve career prospects and build essential skills to achieve a lucrative job role with exciting growth prospects in the future.

 

When students search for study tips and learning methods that can help them improve their habits and grades, experts often talk about focusing and studying one topic at a time.

This is a good strategy if there’s enough time and the topics are not too complex. However, as many students and educators would note, the course content only gets more complicated as the students advance to higher grade levels. Therefore, students have to learn other strategies that will allow them to study various topics while broadening their capacity to understand these complex topics.

What if I told you that you could alternate between topics and reap the same (if not more) learning benefits than if you took one topic at a time?

Related reading: How to Study Using Spaced Practice

What is Interleaving? 

Interleaving is a learning method that involves studying a mix of different topics. This is a systematic mixing of topics—not random. And like any learning technique, the main goal of interleaving (mixing) topics is to improve learning.   

The principles of Interleaving learning can be applied when learning different topics. See an example below:

You have a World History exam coming up, which you have to study for. The exam coverage encompasses Europe during the Medieval and Renaissance periods. This includes the life, society, politics, arts, and culture of the times.

Should you study each topic one at a time, or should you switch between topics? 

Studying for this test using the interleaving method means learning about the history of countries during specific eras (Medieval, Renaissance, etc.) and comparing what was happening in each country and see if there are any connections there. For test preparation, you can use the interleaving method on a subject-specific level. This could mean mixing up the different types of questions per subject.

How the Interleaving Method Works 

When using the interleaving method, it’s not just about picking the most random topics and studying them interchangeably. To maximize the benefits, there has to be a system to it, from setting a goal to the actual implementation of the technique.

Here is an example of how to do it:

  1. Start with a goal in mind. In the case of studying history, one goal can be to understand how the historical events happening in one country can affect other countries.
  2. Choose topics to study. Studying per era and interleaving the historical events of different countries can facilitate a broader understanding of world history.

Note: learners can choose to interleave different topics from one subject (as in the World History example) or choose to study multiple subjects.

  1. Devote enough time for studying each topic. To thoroughly learn and understand a topic, students have to devote a sufficient amount of studying. Do not switch to a different topic or subject should the current one becomes more challenging.
  2. Mix it up by spacing them throughout the week and using a variety of study methods if needed. It is best to follow a schedule as this creates a system for learning.
  3. Make connections between the concepts and ideas that you have learned. This is the most crucial part, as this is the step that adds depth to the learning process.

The interleaving method challenges the brain to constantly retrieve information as students go back and forth between topics. Thus, students are required to access information that is stored in their long-term memory. If anything, this shows that relying on information that is stored in the short-term memory is not sufficient.

What It Is Not

Now that we have explored what interleaving is, it is time to explore it as it relates to other concepts: blocked practice, spaced repetition, and multitasking. 

Blocked practice requires students to study one subject before moving on to the next topic. In a way, it is the opposite of the interleaving method. This is the method that has been discussed in many education and learning circles.

In spaced repetition, the brain is challenged by putting gaps in your study schedule. In the interleaving strategy, the gap is filled in by a different topic—the “spacing” is filled in with a topic that is meant to be mixed with the current one being studied.

Both interleaving and spaced repetition require students to use retrieval practice. In spaced repetition, students have to recall and retrieve information that they deliberately forgot. In interleaving, students have to retrieve the information they previously learned and connect it to the one that they are currently learning. 

Interleaving is not multitasking. It might seem like the same thing on the surface level, but multitasking in learning implies learning a handful of topics on a surface level while not really mastering any of them.

The point of interleaving is to explore various topics that are somehow related to each other that would hopefully lead to mastery of a subject—doing so systematically and following a schedule.  

The Interleaving Technique is Not Always the Best Option

Interleaving is attributed to introducing variety into a student’s study schedule. Instead of studying one topic at a time, they are asked to explore two or more topics and mix them most productively, promoting learning and mastery of a given topic.  

The interleaving method is often compared with blocked practice because these two are different. However, they both serve other functions and cater to the needs of different types of learners. That is to say, interleaving might be effective and efficient, but so is blocked practice.

Students have to have the ability to use different learning strategies when faced with various topics to help them achieve their academic goals. Aside from interleaving and blocked practice, there are other methods like mind mapping, the Leitner method, SQ3R, Feynman technique, among many others. These techniques have their own merit and are designed to help different types of learners. However, there is no one way or one best method that can work for everyone.

Benefits

Interleaving has a lot of benefits for students and adults. While there are many study and learning techniques out there, it wouldn’t hurt to try interleaving, especially if you already have an existing study routine or are good at making and following schedules.

Interleaving requires studying a mixture of topics, and if done regularly (following a plan), it can help students retain information while making connections between concepts.

The interleaving method is said to help develop a person’s capability and capacity for problem solving and categorization. In addition, because students have to study a few topics at one, they learn to differentiate one concept from another. Likewise, it helps strengthen the memory. As they make connections, they have to recall information that they previously learned.

Because students are constantly retrieving information and making connections, various parts of the brain are activated at a single study session. Thus, the interleaving effect is called such as a result of learning better due to using the interleaving method.

In addition, interleaving topics can train people’s brains to differentiate and discriminate between topics that may be similar to each other.

Interleaving helps when studying science and math subjects but can also work for social sciences (as cited in the example above). In a subject like math, where students are taught to use various formulas to solve the same equation, they have to understand the fundamental differences and similarities with the formulas and why one method is more appropriate than the other despite arriving at the same answer. 

On a practical level, the interleaving method is relatively easy to implement into one’s study routine. Students have to study for multiple subjects in a semester anyway. The interleaving method is just one of the ways to put a system to the learning.

These benefits can be helpful even in adulthood and working life. People have to handle multiple projects at once. Students can apply the skills and aptitudes that they learned while doing the interleaving method.

Focusing by taking on multiple topics

Interleaving has a paradoxical benefit in the sense that by mixing topics together, a person is able to focus more so that they can learn and retain as much information while studying one subject. When that happens, they can tap into this information when they study for the next topic and keep accessing it whenever needed.

By extension, interleaving develops students’ ability to transfer skills and knowledge that they learned from one subject area that might be applicable to another.

While doing one thing at a time (in this case, one subject at a time) is almost always associated with boosting focus, so can a carefully planned mixture of topics and questions. 

Final Thoughts

The interleaving method is a learning technique that is labor-intensive at first because it involves careful planning of study sessions and selecting content that will be interleaved. However, this can have long-term benefits as it facilitates higher-order and critical thinking skills. While blocked learning has been spoken so highly about for teaching students to focus, interleaving topics can do the same thing while boosting the learning capacity of students.

The interleaving method may not work for everyone, but students have to at least be aware of the other study methods that they can utilize when what they’re using no longer serves them.