Teach Yourself Computer Science

[tao]

If you’re a self-taught engineer or bootcamp grad, you owe it to yourself to learn computer science. Thankfully, you can give yourself a world-class CS education without investing years and a small fortune in a degree program ?.

 

There are plenty of resources out there, but some are better than others. You don’t need yet another “200+ Free Online Courses” listicle. You need answers to these questions:

• Which subjects should you learn, and why?
• What is the best book or video lecture series for each subject?

This guide is our attempt to definitively answer these questions.

TL;DR:

Study all nine subjects below, in roughly the presented order, using either the suggested textbook or video lecture series, but ideally both. Aim for 100-200 hours of study of each topic, then revisit favorites throughout your career ?.

 

Subject	Why study?	Best book	Best videos
Programming	Don’t be the person who “never quite understood” something like recursion.	Structure and Interpretation of Computer Programs	Brian Harvey’s Berkeley CS 61A
Computer Architecture	If you don’t have a solid mental model of how a computer actually works, all of your higher-level abstractions will be brittle.	Computer Organization and Design	Berkeley CS 61C
Algorithms and Data Structures	If you don’t know how to use ubiquitous data structures like stacks, queues, trees, and graphs, you won’t be able to solve hard problems.	The Algorithm Design Manual	Steven Skiena’s lectures
Math for CS	CS is basically a runaway branch of applied math, so learning math will give you a competitive advantage.	Mathematics for Computer Science	Tom Leighton’s MIT 6.042J
Operating Systems	Most of the code you write is run by an operating system, so you should know how those interact.	Operating Systems: Three Easy Pieces	Berkeley CS 162
Computer Networking	The Internet turned out to be a big deal: understand how it works to unlock its full potential.	Computer Networking: A Top-Down Approach	Stanford CS 144
Databases	Data is at the heart of most significant programs, but few understand how database systems actually work.	Readings in Database Systems	Joe Hellerstein’s Berkeley CS 186
Languages and Compilers	If you understand how languages and compilers actually work, you’ll write better code and learn new languages more easily.	Compilers: Principles, Techniques and Tools	Alex Aiken’s course on Lagunita
Distributed Systems	These days, most systems are distributed systems.	Distributed Systems, 3rd Edition by Maarten van Steen	?‍

Why learn computer science?

There are 2 types of software engineer: those who understand computer science well enough to do challenging, innovative work, and those who just get by because they’re familiar with a few high level tools.

 

Both call themselves software engineers, and both tend to earn similar salaries in their early careers. But Type 1 engineers grow in to more fulfilling and well-remunerated work over time, whether that’s valuable commercial work or breakthrough open-source projects, technical leadership or high-quality individual contributions.

Type 1 engineers find ways to learn computer science in depth, whether through conventional means or by relentlessly learning throughout their careers. Type 2 engineers typically stay at the surface, learning specific tools and technologies rather than their underlying foundations, only picking up new skills when the winds of technical fashion change.

Currently, the number of people entering the industry is rapidly increasing, while the number of CS grads is essentially static. This oversupply of Type 2 engineers is starting to reduce their employment opportunities and keep them out of the industry’s more fulfilling work. Whether you’re striving to become a Type 1 engineer or simply looking for more job security, learning computer science is the only reliable path.

 

If interested, please start < here >.