Stage 4 of 6 · 10 lessons · ~3 months

Data structures and Big-O

Learn the handful of structures almost all code is built from, and how to reason about the time and memory a solution costs. This is what separates code that works from code that still works with a million rows.

Start: Big-O time complexity

Lessons· one lesson for each topic, in this order

Start with· follow one of these

CoursePaid
Grokking Data Structures & Algorithms for Coding Interviews
Design Gurus · Beginner · Subscription
Each structure built from first principles, with solutions in Python, Java, C++, JavaScript and C#
CourseFree
CS50: Introduction to Computer Science
Harvard University · Beginner
Free: weeks 3 and 5 cover searching, sorting, linked lists, hash tables and trees

Practise

Design Gurus Problem Set
Free problems organised by data structure; stick to the easy ones in this stage

Keep handy

VisuAlgo
Step through linked lists, hash tables and sorts with your own input
The Python Tutorial
Chapter 5 on lists, dicts, sets and deque: the built-ins you will use from now on

Also worth your time

Demystifying Big-O Notation: The Ultimate Guide to Understanding Algorithm Complexity (opens in a new tab)Read
Time and space complexity worked through five common algorithms

Before moving on: Implement a stack, a queue and a hash map from scratch in your language, state the Big-O of each operation, and solve 30 easy array and hash map problems you can explain aloud.

Tauseef's advice

Build each structure once by hand, then use the built-in version for the rest of your career. Do not grind hard problems yet: 30 easy ones you can explain are worth more than 150 you copied, and the DSA roadmap takes it further when you are ready.