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A comprehensive, 3-pillar curriculum that builds durable understanding of artificial intelligence and machine learning — from the mathematical foundations and classical algorithms, through modern deep learning architectures, to the societal implications of deploying AI in the real world. Emphasizes timeless principles over transient tools so knowledge remains valuable as the field evolves.

How machine learning actually works — from learning-as-optimization through the classical toolkit to deep learning and foundation models. The depth step after AI Fundamentals: real mechanics, no code or graduate math required.

A working understanding of blockchain and Web3 — what these systems actually are, why they were built, and how the pieces (wallets, consensus, smart contracts, tokens, DeFi, NFTs, DAOs) fit together. The trunk gives you the orientation to follow any crypto conversation; clusters dive into cryptography, custody, consensus, smart-contract engineering, DeFi mechanics, NFTs/DAOs, and building dApps.

A practical, 4-pillar skill track that takes you from zero to shipping. You will learn to think in code, master one language deeply (Python), turn scripts into real software with tests and version control, and put your work in front of users with a deploy, a database, and modern AI-assisted workflows. Deliberately narrower than a role-track CS degree: if the question is 'can I build and ship software,' this is the answer.

A working understanding of discrete mathematics — the math of countable, structural objects: sets, logic, counting, graphs, integers, algorithms. The trunk gives you the toolkit; clusters dive into combinatorics, graph algorithms, number theory, logic and computation, cryptography, and information theory.

The foundation curriculum that prepares you for any university-level math course — calculus, linear algebra, discrete math, statistics. Builds symbolic fluency from variables and equations through functions, polynomials, exponentials, trigonometry, and the proof and set-theory groundwork that modern mathematics rests on.