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Learn Data Structures and Algorithms in Python

Build the data structures yourself, then use them to solve harder problems with less guessing.

What will you learn?

If you've had trouble getting past a hard whiteboarding session, this course is for you. Big-O complexity is arguably the most important concept students learn in a formal computer science degree. You'll build data structures from scratch in Python and improve your problem-solving skills. We'll cover binary trees, linked lists, stacks, graphs and more. This Python course will give you the foundation you need to start your career off on the right foot. After completing this course, you'll be comfortable crushing interview questions and writing performant code.

Chapter List

1
Algorithms Intro
Learn about what algorithms are and why they matter
2
Math
Learn the math required to understand Big-O notation, namely exponents, logarithms, and factorials
3
Big-O Analysis
Figure out what Big-O notation and time complexity mean in the context of algorithms and performant code
4
Sorting Algorithms
Learn how data is sorted on a computer, and how to sort it faster
5
Exponential Time
Understand why exponential time complexity is so dangerous
6
Data Structures Intro
Learn about data structures and how they play a critical role in algorithms
7
Stacks
Learn about stacks, the original LIFO data structure and build one from scratch
8
Queues
Learn about the FIFO queue data structure and how to implement a simple one from scratch
9
Linked Lists
Understand how linked lists vary from arrays and how to use one to build a faster queue
10
Binary Trees
Learn about binary trees, what they are used for, and implement one from scratch
11
Red Black Trees
Solve the classic balancing problem of traditional binary trees with a red-black algorithm
12
Hashmaps
Build a hashmap from scratch and learn how to use the Python dictionary type effectively
13
Tries
Build all the methods of a trie class, and efficiently search entire documents of text
14
Graphs
Learn about graph structures and how we can use them to quickly solve a wide array of search problems
15
BFS and DFS
Implement and understand the ever-famous breadth first and depth-first search algorithms
16
P vs NP
Learn about P and NP

Join 38,680 students in the Learn Data Structures and Algorithms in Python course

Read reviews of their learning experiences

Some of the topics could be quite hard to understand although the dev team tried to break it down, and need additional google search

(4/5)
Kenny Raditia profile image

Kenny Raditia

Singapore

good review

(5/5)
Alex Reynolds profile image

Alex Reynolds

United States

Difficult and had to use some baked salmon, especially for some of the RB trees, but well taught!

(5/5)
Erin K profile image

Erin K

United Kingdom

Sometimes the exercise descriptions can be a bit vague but overall its ok

(4/5)
Djonn Ripero profile image

Djonn Ripero

Ukraine

I believe the concepts in this course are good to know, but it's quite esoteric and not very straightforward to pick up and understand

(4/5)
Ron Ih profile image

Ron Ih

United States

i have a headache

(5/5)
Pablo profile image

Pablo

Argentina

Understanding how data is stored and used is important. Course is a touch opaque at times though. Be ready to do lots of extra research.

(3/5)
Richard K profile image

Richard K

United States

Data Structures and Algorithms is hard. Make sure to spend some time practicing harder Python code (e.g. leet code exercises) before starting.

(4/5)
Sherif Tariq profile image

Sherif Tariq

United States

A good instruction course on how algorithms work. Frustrating at times but rewarding.

(4/5)
Daniel Slaktoski profile image

Daniel Slaktoski

United States

Showing 1-9 of 469

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Mediocrity doesn't cut it anymore

The only way to become a great developer is to write a lot of code

Avoid tutorial hell

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Stay motivated with

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Build portfolio projects

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Delve deeper

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Learn flexibly online

without interrupting your life

For 1% the price of college

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Frequently asked Questions

Got questions? We've got answers

Yes! It's free to create an account and start learning. You'll get all the immersive and interactive features for free for a few chapters. After that, if you still haven't paid for a membership, you'll be in read-only (content only) mode.

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