After this lesson, you will be able to: Understand what computer science fundamentals are, why they show up in technical interviews and production code, and how to take this track.
Computer Science Fundamentals is a parent track with two sub-tracks: Data Structures and Algorithms. These are the ideas behind every piece of software you will ever build, and they are the single most tested topic in coding interviews. This track teaches them practically, with real code in Python and JavaScript, not abstract theory.
This is a free introductory lesson. No purchase required.
Data structures are the ways you organize data in memory: arrays, lists, maps, trees, graphs. Algorithms are the step-by-step procedures you run on that data: searching, sorting, traversing, optimizing. Every program you use is built from these two things. Picking the right structure and the right algorithm is the difference between code that runs in milliseconds and code that times out.
Two reasons. First, interviews: almost every software role, from junior to staff, screens with data structures and algorithms questions on platforms like LeetCode and HackerRank. Knowing this material is how you pass those screens. Second, real work: when your API is slow, when a query takes ten seconds, when a feature does not scale, the fix is almost always choosing a better data structure or algorithm. This is not academic. It is the toolkit that separates engineers who guess from engineers who reason.
Take Data Structures first. It teaches you the containers: how arrays, linked lists, stacks, queues, hash tables, trees, heaps, graphs, and tries work, and what each one costs. Then take Algorithms. It teaches the procedures: Big O analysis, binary search, sorting, recursion, dynamic programming, greedy methods, graph algorithms, string patterns, and backtracking. The Algorithms sub-track leans on the structures you learned first, so the order matters.