Everyday Mental Health

A working understanding of how economies actually behave — how scarcity drives choice, how markets allocate resources (and fail to), how money and policy steer the macroeconomy, and how trade, behavior, and institutions shape long-run prosperity. The trunk gives you the throughline a literate citizen needs; clusters dive into elasticity, market failures, consumer/producer theory, monetary and fiscal policy, trade policy, behavioral finance, and economic history.

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 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 non-technical curriculum that builds real understanding of AI — how it works, why it fails, and how to use it intelligently. No math, no code, just durable mental models that make you a confident, critical user of AI tools.

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.

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.