Know Yourself

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 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.

A career-spanning roadmap from absolute beginner to job-ready mid-level software engineer. The trunk gives you the complete throughline — the concepts, languages, systems, and professional skills every engineer needs — and clusters let you go deep on specific topics (Python, React, Kubernetes, system design, security, career strategy) when they matter.

A beginner-friendly curriculum that builds deep intuition for how AI actually works — not through math or code, but through mental models that make effective use a natural consequence of understanding. Covers how language models think, why they hallucinate, the art of prompting, practical AI workflows for writing, images, and code, and the societal shifts AI is driving. Designed for anyone curious enough to want more than tips and tricks.

A working understanding of linear algebra — vectors, matrices, eigenvalues, and the decompositions that power modern data, graphics, and AI. The trunk gives you the geometric and algebraic core; clusters dive into vector spaces, systems and rank, eigentheory, orthogonality and projections, applications, and numerical computation.

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.