How you store and search your data decides how clean and how fast a program turns out. Data structures are the containers that hold your data, and algorithms are the step-by-step methods you use to work with it. Knowing which to pick is a core skill for every Python developer.
You'll start with Python's built-in collections: lists, tuples, and sets for ordered and unique values, and dictionaries for fast key-value lookups. Then you'll learn Big O notation, the standard way to describe how an algorithm's cost grows with the size of its input, and put it to work with binary search, a classic algorithm that finds values in sorted data far faster than checking every item.
With these tools in hand, you'll be ready for the next module, OOP & Functional Python, where you'll learn to organise your code with classes and functional techniques.
How lists and tuples hold ordered data and sets hold unique values, with the key methods for each and when to choose one over another.
Storing data as key-value pairs, using dictionary methods, adding and removing entries, and looping through keys and values.
A beginner-friendly look at time and space complexity, and how Big O notation lets you compare how algorithms scale as input grows.
How binary search repeatedly halves a sorted list to find a value quickly, with a step-by-step implementation in Python.