The top-level map for the CS notes. Each area below has its own index that lays out how its topics fit together. Pick one and drill in, or use the sidebar and graph view to browse directly.
Foundations and theory
- Data Structures & Algorithms - representing data and designing algorithms that scale.
- Programming Language Concepts - how languages are defined, evaluated, and typed.
- Mathematics - the discrete mathematics underneath the rest of CS.
- Statistics - probability and inference for data and machine learning.
Machine learning and deep learning
- Machine Learning - learning from data: paradigms, training, and honest evaluation.
- Deep Learning - neural networks with depth, from the perceptron to CNNs, sequence models, generative models, and reinforcement learning.
Systems and software
- Systems - operating systems, networks, and how machines actually run programs.
- Software Engineering - building and maintaining software that lasts.
- Languages - one question, generics, answered five structurally different ways across nine languages, plus the concerns every real language must answer.
- Standards - the documents that govern the technologies above: the 802 family, IEEE 754, POSIX, and the process standards engineering runs on.
Security and networking
- Security - cryptography, attacks, defenses, and the systems that hold under adversarial pressure.
- Networking - how packets, protocols, and routing carry data between machines.
- Cisco - the vendor layer: IOS, switching, routing, and security appliances in practice.
- Law - what the law permits, forbids, and compels when systems are attacked, defended, searched, or exported.
- Forensics - turning what happened on a machine into evidence a third party will believe.
Resources
- Resources - vetted free and open books, courses, papers, code, and talks behind these notes.
History and context
- History of Computing - the arc from the Antikythera mechanism to deep learning.
- Computing & the U.S. Military - how computing evolved through military history.
- Geopolitics - security, sovereignty, and the politics of technology.
- Ethics of AI & Big Data - whether a machine can be a mind, and what we would owe it if it could.