UC Berkeley CS 61A

Category

Core CS

Provider

UC Berkeley

Type

course

Level

intermediate

Topic

Core CS

Track

Core CS

Section

n/a

Format

['text']

Status

publishable

Commercial

unknown

Featured

no

Fast start

no

Sequence

n/a

Priority

n/a

Primary source

learning_paths

Sources

learning_paths

ID

ab0f808d435e5ed2

Teach Yourself Computer Science

teachyourselfcs.com

Gap-filling map after bootcamps/self-teaching.

SICP (Structure and Interpretation of Computer Programs)

MIT Press

Mental models for abstraction, interpreters, and computation.

MIT 6.042J: Mathematics for Computer Science

MIT OCW

Discrete math, proofs, probability, graphs, and recurrences.

Stanford CS229: Machine Learning

Stanford

Solid mathematical and algorithmic treatment of core ML.

scikit-learn documentation

scikit-learn

Still the fastest way to build strong baselines and classical ML systems.

Nand2Tetris

Nand2Tetris

One of the best bottom-up systems courses ever made.

Google Machine Learning Crash Course

Google

High-signal introduction to supervised learning, feature engineering, evaluation, and modern ML workflow.

fast.ai Practical Deep Learning for Coders

fast.ai

Best practical route from beginner coder to shipping models quickly.

web.dev Learn Performance

Google

Beginner-friendly performance course for building fast, user-friendly websites.

Stanford CS231n

Stanford

Still one of the best deep learning for vision courses.

Stanford CS224n

Stanford

Strong sequence-modeling and language modeling foundation.

scikit-rf

scikit-rf

RF/microwave network analysis in Python; foundations for signal integrity work.