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Thinking of a career in computer science – but not exactly sure which exact path you should follow?

You may want to consider a career in artificial intelligence.

Artificial intelligence is a field that focuses on the simulation, inference, and representation by software and computers as they relate to human learning, reasoning, and processing. It’s a major that’s quite similar to other specializations in computer science, like animation, data science, and robotics.

However, this field is one that is currently on the rise. As more companies expand and adopt various technologies across industries, they need trained professionals to help them with the transition. It’s anticipated that artificial intelligence will create close to 2.3 million jobs by the end of the year!

There are plenty of career opportunities in artificial intelligence, or AI, and earning an online artificial intelligence certification has never been easier. You’ll just need to find the right online training program.

Here’s what you need to know. 

 

What Exactly is Artificial Intelligence – and Why Does it Matter?

What Exactly is Artificial Intelligence

Artificial intelligence is the way we make intelligent machines. If you’re new to this field, you might wonder if AI is the same thing as making self-aware robots! Rest assured, you don’t have to get involved with the makings of a sci-fi movie in order to pursue one of these careers.

AI is simply software that learns in a manner similar to how humans learn. The software mimics the human learning process so that it can take over some of mankind’s most mundane jobs – or find ways to do them better or faster.

A common subset of artificial intelligence is machine learning, which is the process by which AI learns. With machine learning, algorithms are developed that then use various modules of training data to help computers learn something they aren’t already programmed to do.

That’s not all, though. Machine learning is simply the first stage in the AI process. Stage two is machine intelligence – in this stage, machines learn from past experience based on false algorithms. Stage three is machine consciousness, which is when systems can self-learn from their experiences without users having to put in any external data (an example would be Siri).

There are plenty of benefits to using AI, and it has applications in a variety of industries. You probably use AI already, perhaps without even realizing it. You use it to find your destination via ride-sharing apps and it’s found in all of your smart home devices.

From a business standpoint, companies can use AI to assess risk and to cut costs, boost innovation, and develop new opportunities.

 

What Skills Do You Need for a Career in Artificial Intelligence?

When you first start exploring degree options for your potential career in artificial intelligence, you may find yourself wondering what kinds of classes are required.

It can often be more helpful for you to think about what kinds of artificial intelligence topics and skills you will need to master instead. Many universities offer full majors or courses in artificial intelligence, but they usually each refer to courses and describe them in varying ways (despite more or less all covering the same content).

Instead, it can be helpful for you to think about what skills you would like to have by the time you finish your degree (rather than just a list of classes).

You can break down these skills into two categories – soft and hard.

“Soft” Skills for Artificial Intelligence Careers

Soft skills can be difficult to define and evaluate – usually, if you’ve got them, you’ve got them, and if you don’t, you don’t. They are very tricky to learn, as they usually are innate characteristics that are developed over time (rather than something that is taught directly in a college program, for example).

Examples of soft skills include listening skills, communication skills, and collaboration skills.

When you work in artificial intelligence, you will need to be able to think analytically. You’ll have to become good at solving problems, particularly by utilizing efficient and cost-effective solutions.

Not only that, but you’ll need to be able to apply some strategic foresight about potential technological innovations. These will later translate to state-of-the-art programs that businesses can develop and use to stay competitive in a constantly changing global marketplace.

Good communication skills are also essential for AI professionals, and this is something that many prospective students overlook. When you begin a career in artificial intelligence, you won’t just be sitting in front of a computer all day (although that is part of it). You will also need to be able to communicate with others.

It won’t just be water cooler talk, either. You’ll need to learn how to translate highly technical information to others (typically those who have limited or nonexistent technical backgrounds) so that they can then carry out their jobs. You will need to be able to do this in both a written and verbal format.

You will also need to have soft skills and personal traits like perseverance, discipline, confidence, and curiosity.

“Hard” Skills for Artificial Intelligence Careers

Beyond those “soft” skills, you will also need some serious technical skills. You will need to know how to create, maintain, and fix various software and technology programs.

Some examples of hard skills you’ll need to master include:

  • Machine learning theory
  • Software engineering
  • Machine learning frameworks
  • Programming languages
  • Cloud platforms
  • Big data tools
  • Natural language processing tools
  • Workflow management systems
  • Statistical inference
  • Domain-level knowledge

 

Which Online AI Classes Should You Take?

To get started in AI, you’ll need to first consider your current level of expertise. Are you starting fresh outta high school, with no prior experience in the field? Or are you already working in programming or data science? If you have a computer science background, you may be able to skip one of the core course requirements.

Otherwise, you’ll need to take a variety of general studies and liberal arts courses. Get these under your belt as quickly as possible so you can then move on to more relevant topics.

Because artificial intelligence consists of several different overlapping disciplines, it may be easier for you to pursue the following online AI classes if you already have a background in computer science. Taking interdisciplinary courses in topics like cognitive science can also give you a strong conceptual framework for AI applications.

Some of the following classes will prove to be helpful as you start your journey in artificial intelligence.

Statistics

Some people argue that artificial intelligence (particularly machine learning) is nothing more than statistics in disguise. To some extent, that’s true – although it’s more advanced than that, to say the least.

Many machine learning techniques and algorithms either rely on heavily or are completely bored from statistics. Therefore, it’s important that you take and master courses like statistics in order to be successful in this field. Ideally, you should get several statistics classes under your belt before moving on to more advanced topics in artificial intelligence.

Linear Algebra

Linear algebra is essential for mastering machine learning, a key component of artificial intelligence.

English

Wait, English? Really? You might be surprised to see this class on the list of required classes for artificial intelligence majors. However, it’s essential. Even a few basic college English courses can help you succeed in artificial learning.

Why?

Well, think back to those communication skills we told you that you need. Without knowing how to communicate – and how to communicate not just with other AI professionals, but with those who have no understanding of the discipline – you won’t be very successful in your career.

Probability

Probability is important for artificial intelligence because you need to get acquainted with variance, random variables, expectations, Markov chains, Bayesian inference, and other crucial aspects of probability.

Calculus

Unless you’ve just finished up an associate’s degree or a bachelor’s degree in another area, you’re probably going to want to brush up on your calculus skills. Calculus, along with integration (both necessary for probability topics in artificial intelligence) is absolutely essential.

You will likely take not just one, but a couple of courses in calculus before you complete your studies.

Algorithms

Algorithms

In order to bring your ideas in artificial intelligence to life, you will need to master algorithms. These classes can be quite rigorous, and you’ll likely take more than one class in algorithms before you are finished with your studies. The best courses in this key artificial intelligence topic will be those that let you do a great deal of hands-on work.

Physics

Physics is another prerequisite course that can help you get ahead in artificial intelligence. It will let you get some insight into some of the most common machine learning concepts used in artificial intelligence. It can give you a good framework for understanding more abstract concepts from information theory and probability, too.

 

Artificial Intelligence Principles and Techniques

Many students will begin their studies in artificial intelligence by taking an introductory overview of the discipline first. This class will provide students with information on how AI can be used to solve problems, reason, learn, and interact. As the course progresses, it usually enables students to design, test, and implement some basic algorithms.

As an introductory course, this one should be at the top of every aspiring AI professional’s list. It will give you a good idea of whether this career path is right for you.

Bayesian Networking

This course deals with a type of representation and reasoning system that is often used in artificial intelligence. In this course, you’ll learn how to both construct and analyze Bayesian networks.

Graphical Modeling

This course deals with graphical models, which combine graph and probability theories. In doing so, they create a more flexible framework for modeling substantial collections of random variables with complex interactions you might find in artificial intelligence.

Spark and Big Data Technologies

You may take some classes that will help you deal with large volumes of data, any of which could be streaming or real-time production-level data. You will need to know about big data technologies, like Apache Spark, Hadoop, MongoDB, and Cassandra.

AI Representation and Problem-Solving

This class deals with modern techniques that help computers represent task-relevant information to make intelligent decisions toward goal achievements. You’ll research all kinds of AI questions like how to represent knowledge and deal with uncertainty in the modern (and future) AI world.

Robotics

Robotics

Depending on your ultimate career focus, you may take one or more classes in robotics, too. Most students take at least a few. These classes are important because they will acquaint you with the basic tools and methodologies in robotics research, as well as applications that can be used for further experimentation in this field.

Some key topics within this sub-discipline that you’ll cover include statics, kinematics, spatial descriptions, and motion planning, just to name a few.

Cognitive Science Theory

This Is a highly interdisciplinary course that will acquaint you with the ways in which the mind works by using various tools and insights from fields like computer science, vision science, neuroscience, behavioral economics, and more.

Computer Science, Programming Languages, and Coding

You’ll need to learn several different programming languages in your artificial intelligence journey. While there are all kinds of languages that computer science majors might master, one of the most common for aspiring AI professionals is Python.

You might also take classes to help you master programming languages like C++, Java, and R, too, to help you design and implement models.

You’ll also need to gain skills in areas like algorithmic thinking and coding.

Machine Learning, Deep Learning, and Reinforcement Learning

Machine learning – along with deep learning and reinforcement learning – is a crucial part of most artificial intelligence programs. This topic will help you gain mastery of things like supervised and unsupervised learning in addition to learning theory, control, and reinforcement learning.

You might also learn some of the applications of machine learning technologies, too.

Information Theory, Inference, and Learning Algorithms

This class is important for machine learning and covers everything from probability to information theory. You’ll also cover concepts like Monte Carlo methods, high-dimensionality, variational methods, and Bayesian model comparison in this class, too.

Natural Language Processing

Natural language processing deals with the algorithms that are available for processing linguistic information – as well as the computational properties of those languages. This discipline normally takes deep learning approaches like debugging, training, and implementing neural network models.

Computer Vision and Image Analysis

Computer vision and image analysis are course topics that deal with the many applications of computer vision like cameras and projection models.

An online artificial intelligence course in this topic might cover low-level image processing methods like edge detection and filtering or mid-level vision topics like clustering and segmentation. This course topic also generally covers things like face and human motion detection and categorization.

Logic Programming and Computational Logic

This course is essential as it shows learners how to encode information in logical sentences. Logic is necessary in any machine learning environment. As you are enrolled in an AI program, you may take a very basic version of this course or one that is very advanced.

You’ll learn how logic technology can be applied to various disciplines, including business, science, law, engineering, mathematics, and more. You’ll learn about processes of natural and mathematical deduction and induction along with the semantics of Herbrand Logic, Relational Logic, and Propositional Logic.

Deep Learning

Deep Learning

Deep learning is a highly-sought-after skill in AI, and this class is usually included (at the very least, as an electron) in most online artificial intelligence programs.

You’ll learn how to build neural networks and lead successful machine learning projects in this class. You’ll also learn the foundations of deep learning before moving on to learn about convolutional networks.

Some online artificial intelligence courses make it possible for you to give into case studies, too, so you can see how theory is applied to an actual industry setting.

Agile Software Development

As an aspiring artificial intelligence major, you can choose a program that offers a specific major in artificial intelligence or pursue a major like graphic design, computer science, health informatics, engineering, or information technology – but with a specialization in artificial intelligence.

Some other classes you can take, either as core courses or electives, might include:

  • Data Science Essentials
  • Principles of Imperative Computation
  • Parallel and Sequential Data Structures and Algorithms
  • Neural Computation
  • Cognitive Robotics
  • Speech Processing
  • Vision Sensors
  • Machine Learning for Text Mining
  • Advanced Data Analysis
  • Safe and Interactive Robots
  • Designing Human-Centered Systems

What Kinds of Careers Are Available in Artificial Intelligence?

Artificial intelligence is being used in a variety of industries – some of them might surprise you. Quite a few large brands are already in the trenches when it comes to adopting artificial intelligence, including Amazon, IBM, Accenture, and Microsoft. They use AI to drive innovation.

However, artificial intelligence is also used in sectors like transportation (it can help Uber drivers navigate their routes, for example) and in predictive maintenance for self-driving cars.

Some of the most common artificial intelligence careers include those as :

  • Software developers
  • Computer scientists
  • Software analysts
  • Computer engineers
  • Algorithm specialist
  • Surgical technicians (working with robotic tools)
  • Manufacturing or electrical engineers
  • Research scientists
  • Data analyst
  • Machine learning engineer
  • Data scientist
  • Business intelligence developer
  • Big data engineer or architect
  • Mechanical engineers
  • Engineering consultants
  • Maintenance technicians
  • Graphic art designers
  • Military and aviation electricians

In addition to the industries and careers mentioned above, there are several subsets of AI for you to be aware of, too. Taking some of the specialized online artificial intelligence courses that we told you about above can help prepare you for these “niche” areas.

For example, neural networks are used to help software learn how to recognize and classify information. They can make decisions with a high level of accuracy based on the data that is inputted.

Natural language processing is another subset of AI. This provides machines with the ability to understand human language. Machines learn to respond in ways that human audiences can comprehend. Deep learning is yet another area of AI that continues to be explored. It focuses on machine learning tools and how we can deploy them to solve problems and make decisions.

If these careers all sound quite different, that’s because they are. Although there are similarities between these various careers and subsets in artificial intelligence, you’ll find that they all share various communities.

One thing is for sure, though. Beginning a career in artificial intelligence is a smart choice, particularly if you enjoy working with technology and have the mathematical and technical skills necessary to succeed. The pay isn’t too shabby, either – on average, artificial intelligence professionals earn more than $134,135 per year.

 

Should I Pursue an Online Artificial Intelligence Course of Study?

If you’re thinking of pursuing a career in artificial intelligence, know that there are plenty of ways for you to meet your goals. If you’re already in the workforce, earning a degree is not out of the question. You’ll just need to find more flexible ways to meet your goals.

Earning an online degree is a great place to start. By studying online, you’ll be granted the flexibility and convenience necessary to complete your coursework whenever it fits into your schedule.

Online learning opportunities are booming, too. All kinds of schools, including MIT, Stanford, and Carnegie Mellon, have preset tracks for people who want to work in AI.

If you don’t want to enroll in a full-fledged program, you don’t have to either – there are various supplemental programs out there that can help someone who is mid-career retrain to transition into a new career in artificial intelligence.

Even companies like Microsoft are offering specialized AI programs. The AI track for the Microsoft Professional Program offers programs online to anyone and provides relevant job-ready skills in AI and data science.

Taking even just one online artificial intelligence course can provide you with the online training you need to succeed. Consider signing up for a few of these classes today – or enrolling in a full-fledged AI programming degree.

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Anthony Cornell

Anthony Cornell is a freelance technology journalist. He reviews educational software and writes in-depth online course reviews from popular e-learning platforms. You can reach Anthony at anthony@learnacourseonline.com

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