Free Computer Science Education

The classic MIT course on programming fundamentals using Scheme, exploring abstraction, recursion, and interpreters. Taught by Hal Abelson and Gerald Jay Sussman.

David Malan's legendary intro course. Covers C, Python, SQL, web development, and more. Known for its high production value and engaging lectures.

Stanford's introductory programming course taught in Java. Focuses on software engineering principles, good coding practices, and problem decomposition.

MIT's modern intro course using Python. Covers computational thinking, data structures, algorithms, and plotting. Taught by Ana Bell and Eric Grimson.

Covers fundamental algorithms including sorting, hashing, graph algorithms, and dynamic programming. A cornerstone MIT course taught by Erik Demaine and others.

Tim Roughgarden's acclaimed course on algorithm design. Covers divide-and-conquer, graph search, shortest paths, greedy algorithms, and NP-completeness.

Robert Sedgewick and Kevin Wayne's two-part course on Coursera. Covers stacks, queues, trees, graphs, string processing, and more. Companion to their textbook.

The advanced follow-up to 6.006. Covers randomized algorithms, amortized analysis, network flow, linear programming, and approximation algorithms.

Build an operating system from scratch using xv6, a simple Unix-like OS. Covers virtual memory, interrupts, file systems, and networking at the kernel level.

John Kubiatowicz's comprehensive OS course. Covers threads, synchronization, scheduling, memory management, I/O, file systems, and distributed systems.

The companion lectures for the popular free OSTEP textbook by Remzi and Andrea Arpaci-Dusseau. Covers virtualization, concurrency, and persistence.

Andy Pavlo's highly regarded course on database internals. Covers storage engines, buffer management, indexing, query processing, concurrency control, and recovery.

Jennifer Widom's database course covering the relational model, SQL, constraints, triggers, views, authorization, indexes, and transactions.

The follow-up to CMU 15-445. Covers in-memory databases, MVCC, query compilation, vectorized execution, and modern analytical systems.

Andrew Ng's foundational ML course. Covers supervised learning, unsupervised learning, deep learning basics, generalization, and reinfortic learning. The gold standard for ML education.

Patrick Winston's classic AI course. Covers search, constraint propagation, learning, neural nets, genetic algorithms, and support vector machines. A historical gem.

Jeremy Howard's top-down approach to deep learning. Build real models from day one, then learn the theory. Covers CNNs, NLP, tabular data, and collaborative filtering.

Fei-Fei Li and Andrej Karpathy's deep learning course focused on convolutional neural networks and computer vision. Covers backprop, training tricks, detection, and segmentation.

Philip Levis and Nick McKeown's networking course. Covers the internet architecture, transport protocols (TCP/UDP), routing, switching, and network applications.

MIT's graduate networking course covering congestion control, routing, network architecture, and research topics in computer networking.

Jim Kurose's video lectures companion to the famous 'Computer Networking: A Top-Down Approach' textbook. Clear, well-structured coverage of all networking layers.

MIT's security course covering buffer overflows, privilege separation, web security, network security, side-channel attacks, and building secure systems.

Dan Boneh and John Mitchell's security course. Covers web attacks, network security, malware, OS security, and the foundations of applied cryptography.

The definitive online cryptography course. Covers symmetric encryption, public key crypto, hash functions, authentication, and key management. Available on Coursera.