Project Management

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 the natural world — what science is, how matter and energy behave, how life persists and changes, and how Earth and the cosmos fit together. The trunk gives you a single coherent throughline across physics, chemistry, biology, and earth/space science; clusters dive into experimental design, mechanics, thermodynamics, electromagnetism, modern physics, genetics, ecology, and climate.

Build the universal mental model that every database is implemented against — the relational model, schemas and keys, indexes, transactions, concurrency, PostgreSQL architecture, production operations, modeling patterns, and the modern data ecosystem (NoSQL, distributed SQL, warehouses, vectors, streaming).

The financial life skills nobody actually taught you — money psychology, budgeting, debt, credit, taxes, insurance, retirement accounts, and the math of financial independence. Walk the trunk and you have a system; pull on a cluster when something specific matters.

A working understanding of mathematics — the universal language scientists, engineers, and quants use to describe the world. The trunk gives you the throughline from how mathematicians think to how math models reality; clusters dive into proof, trig, calculus mechanics, advanced linear algebra, number theory and cryptography, probability, stochastic processes, and the foundational limits of math itself.

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.