Data Structures Tutorial

This course is for people who can write basic Python (loops, functions, lists and dicts) and want to stop guessing which container to use. It suits self-taught developers preparing for coding interviews, students who met these topics in a lecture and never quite connected them to code, and working developers whose program is mysteriously slow once the input gets bigger.

You will learn to measure the cost of an operation by counting the work it does, to choose between a list, a deque, a set, a dict and a heap based on the operations you actually need, and to build a small hash table yourself so that dict stops being magic. You will also traverse trees with recursion and with a queue, and use heapq for priority scheduling and top-k problems.

The lessons run from the idea to the tools: first how to reason about cost and pick a structure, then stacks and queues, then hash tables, then trees and heaps. Every snippet is complete Python that you can run, and each output shown was produced by running that exact code. Once you finish, continue with Arrays and Strings for the array-shaped problem patterns and Sorting Algorithms for ordering data efficiently.