Courses DataCamp

Data Structures and Algorithms in Python

Explore core data structures—linked lists, stacks, queues, hash tables, trees, and graphs—and implement key search and sort algorithms in Python while analyzing their efficiency using Big O notation.

Advanced Level 4h 0m 4.70 (841) 🌐 EN

What you'll learn

  • Recognize and implement common data structures: linked lists, stacks, queues, hash tables, trees, and graphs
  • Apply search algorithms such as linear search, binary search, depth-first search, and breadth-first search
  • Use sorting algorithms including bubble sort, selection sort, insertion sort, merge sort, and quicksort
  • Analyze algorithm efficiency with Big O notation for time and space complexity
  • Sharpen Python programming skills through hands-on exercises and practical examples

Skills you'll gain

  • Assess the effect of recursion and dynamic programming techniques on algorithm performance in Python examples
  • Differentiate among bubble sort, selection sort, insertion sort, merge sort, and quicksort in terms of procedure and efficiency
  • Distinguish between linear search, binary search, depth-first search, and breadth-first search based on logic and performance
  • Evaluate time and space complexity of algorithms using Big O notation
  • Identify and choose appropriate Python data structures—linked lists, stacks, queues, hash tables, trees, or graphs—for given problems

Prerequisites

  • Introduction to Object-Oriented Programming in Python

Who this course is for

  • Python programmers who want to deepen their understanding of data structures and algorithms
  • Learners preparing for technical interviews or advanced programming roles
  • Developers who have completed an introduction to object-oriented programming in Python
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