Python Data Structures and Algorithms: Complete Guide

<div>Master the foundations that power real-world Python.</div><div><br></div><div>Write sorting routines and build important data structures from scratch, then discover the Pythonic way to use them in practice. Write unit tests to validate your code. Master Python's special "dunder" methods.</div><div><br></div><div>Why this course?</div><div><br></div><div>If you’ve already learned the Python language (for example through Tim Buchalka’s Learn Python Programming Masterclass, rated 4.6/5 from over 100,000 reviews and taken by more than 430,000 learners), this new Python Data Structures and Algorithms course is the next logical step. It takes you from I can write Python to I can design efficient Python, using the data structures and algorithms employers expect.</div><div><br></div><div>You’ll be learning with Tim Buchalka and JP (Jean-Paul) Roberts, both highly experienced instructors. Tim is a Udemy Instructor Partner with over 1.7 million students and more than 460,000 reviews across his courses. JP brings his industry insight as a co-instructor, ensuring a practical, robust, and engaging learning experience. Their combined expertise means you can feel confident in the quality of this new course, even before reviews come in.</div><div><br></div><div>What makes this course different?</div><div><ul><li><span style="font-size: 1rem;">Build first, then go Pythonic. Each topic follows a clear pattern: theory, your own code, then Python’s built-in tools like sorted(), heapq, deque, and queue.</span></li><li><span style="font-size: 1rem;">Hands-on, job-relevant coverage. Arrays, linked lists, stacks, queues, hash tables, sets, trees, heaps, searching, and sorting are all taught with Big-O analysis and unit tests. You’ll always know your code is correct.</span></li><li><span style="font-size: 1rem;">Up-to-date Python. The course covers modern improvements in CPython, including Python 3.11’s Powersort for list.sort(), with comparisons to earlier approaches.</span></li></ul></div><div><br></div><div>What learners say about Tim and JP’s teaching:</div><div><br></div><div>Note: These quotes reflect students’ experiences from the Python Masterclass. As this Python Data Structures and Algorithms course is newly published, reviews for this course will appear soon.</div><div><br></div><div>“Not slow, just the right speed if you already know programming… Excellent trainer thus far.” – Linda</div><div><br></div><div>“Great, thorough explanations. Very complete. Thank you!” – Anthony</div><div><br></div><div>“Exceptionally good… Really well done!!!” – Rakshan</div><div><br></div><div>Is this course for you?</div><div><ul><li><span style="font-size: 1rem;">Yes: If you already know basic Python and want to think like a software engineer—choose the right structure, reason about performance, and write clean, correct code.</span></li><li><span style="font-size: 1rem;">Yes: If you’re preparing for coding interviews or want efficient, practical patterns for real projects.</span></li><li><span style="font-size: 1rem;">No: If you’re brand-new to Python. Start with the Masterclass, then return here.</span></li></ul></div><div><br></div><div>What you’ll learn</div><div><ul><li><span style="font-size: 1rem;">Foundations and Big-O: What data structures and algorithms are, time and space complexity, and trade-offs.</span></li><li><span style="font-size: 1rem;">Arrays and lists: Memory model, resizing, slicing, iteration, and dunder methods for Pythonic sequences.</span></li><li><span style="font-size: 1rem;">Linked lists: Singly/doubly linked lists, insert/delete, reverse, iterate, indexing, and slicing.</span></li><li><span style="font-size: 1rem;">Stacks, queues, deques: Manual implementations, plus Python’s deque and queue.</span></li><li><span style="font-size: 1rem;">Hash tables and sets: Open addressing, chaining, dict and set, and specialized collections.</span></li><li><span style="font-size: 1rem;">Trees: Binary search trees (insert/search/delete), traversal strategies, fully implement a red-black tree.</span></li><li><span style="font-size: 1rem;">Heaps and priority queues: Build heaps, Heapsort, and Python’s heapq.</span></li><li><span style="font-size: 1rem;">Searching: Linear vs. binary search (iterative and recursive).</span></li><li><span style="font-size: 1rem;">Sorting: Bubble, selection, insertion, merge, quick, counting, radix, and Powersort in Python.</span></li><li><span style="font-size: 1rem;">Testing and correctness: Write comprehensive unit tests with unittest, inspired by CPython’s testing style.</span></li><li><span style="font-size: 1rem;">Abstract Base Classes and Protocols: Use both and understand the differences between them.</span></li><li><span style="font-size: 1rem;">Recursion: When to use it and, importantly, when it's not appropriate.</span></li></ul></div><div><br></div><div>Your learning experience</div><div><ul><li><span style="font-size: 1rem;">Code-along videos that take you from fundamentals to advanced structures.</span></li><li><span style="font-size: 1rem;">Challenges and solutions so you can cement your understanding.</span></li><li><span style="font-size: 1rem;">Production patterns that map directly to Python’s standard library, ready for work environments.</span></li></ul></div><div><br></div><div>FAQ</div><div><br></div><div>Will I both implement algorithms and use Python’s built-ins?</div><div>Yes. You’ll start by building your own, then master robust standard-library tools for production.</div><div><br></div><div>Does the course cover modern CPython sorting?</div><div>Up-to-date Python. The course covers modern improvements in CPython, including Python's assignment expressions (the walrus operator) and Powersort for list.sort(), with comparisons to earlier approaches.</div><div><br></div><div>Is there a refund policy?</div><div>Yes. Udemy offers a 30-day refund window on eligible courses.</div><div><br></div><div>Enroll now</div><div><br></div><div>Join the next step in your Python journey and learn the data structures and algorithms that make great Python code possible from first principles to production-grade patterns with Tim Buchalka and JP Roberts guiding your way.</div>

What you'll learn:

• Develop problem-solving and debugging skills essential for coding interviews.
• Apply algorithmic thinking to real-world tasks, writing efficient and readable Python code.
• Strengthen confidence in data-driven programming and technical interview readiness.
• Implement core data structures like arrays, stacks, queues, and linked lists from scratch in Python.
• Understand algorithm efficiency and analyze code performance using Big-O notation.
• Build and compare sorting and searching algorithms including merge, quick, and binary search.
• Design and implement trees, heaps, hash tables, and other advanced data structures.
• Use Python’s built-in tools effectively, such as heapq, deque, and sorted().