Course Catalog

Teaching Computing
Differently.

6 original community-college courses across AI, systems, mathematics, and engineering, plus 4equity-overlay adaptations of Andrew Ng’s Coursera sequence. Every course is project-based, grounded in learning science, and designed to be free of exams and required textbooks. A proposal in development — not a currently taught program.

6Original

4Ng Adapted

3Tracks / Course

0Exams

11catalog entries total — filter below by status, category, or keyword.

11 Courses Found

Introduction to Artificial Intelligence

AI is not magic — it is math, history, and human choice. We build from first principles: probability, search, neural networks, language models. Then we ask who built these systems, for whom, and what they're encoding about the world.

Introduction to Machine Learning

ML algorithms are not neutral mathematical facts — they are choices about what to optimize, whose data counts, who bears the error. We derive every algorithm before using it, implement from scratch before touching any library.

Data Structures & Algorithms

Every data structure is an argument about the world. Every algorithm is a strategy, a tradeoff, a value judgment. We implement every structure before using the library version. No LeetCode grind — deep projects that transfer.

How Things Work

PageRank. GPS. The phone in your pocket. Three technologies derived from first principles. Includes signature project: Build a Computer from Scratch.

Introduction to Applied Linear Algebra

Six fundamental problems. Twenty-nine lessons. Build circuits, collect data, verify models. Derive before compute — the ALAF approach.

Programming & Problem Solving in MATLAB

Model real circuits. Understand why 0.1 + 0.2 != 0.3. MATLAB the way engineers use it — from binary to IEEE 754. No prior programming required.

AI For Everyone — Civic AI Literacy for All

Andrew Ng's landmark course redesigned for community college. Three tracks from no-prereq literacy to building with APIs. Community audit projects.

Machine Learning Specialization — Every Algorithm is a Choice

Ng's ML specialization rebuilt for community college. Derive before compute. Implement before import. Audit before deploy.

Deep Learning Specialization — Build What You Can Explain

Ng's five-course DL specialization for community college. Six modules, neurons to transformers. Implement backprop from scratch. Mandatory bias audit.

Generative AI For Everyone — Prompts are Arguments

Every image is a choice. Every output reflects training data. Use gen AI critically, build skillfully, audit rigorously.

Build a Computer from Scratch

A 20-week project: teams build a working 8-bit computer on breadboards from logic gates. Cross-STEM transfer across 5 disciplines. Inspired by Ben Eater.

Teaching Philosophy

Every concept is earned through building. Every student is the world's leading expert on their own learning.

Community College CS
All resources free · Open access
No required textbooks
henry@henryfan.org