The library.
The references our instructors actually use. Curated reading lists, lecture transcripts, source-code archives, and the canonical papers worth reading twice.
What's in the stacks
Reading lists
Per-course lists curated by the instructor. Books, papers, blog posts — annotated with why each one matters.
Lecture transcripts
Every video has a clean, searchable transcript. Downloadable as Markdown for note-taking and review.
Code archive
Every code sample, every solution, every starter project — versioned in our public GitHub org.
Capstone showcase
Five years of student capstone projects, browsable by course. Real source code, real write-ups.
Featured reading lists
Modern Web Dev — Year One
32 books, papers, and posts in dependency order. Built by Sarah Chen across three cohorts.
Open the list→Data Science Foundations
Statistics, linear algebra, and Python — what to read before any ML course makes sense. By Dr. Marcus Rivera.
Open the list→Distributed Systems Canon
Twelve papers and three books that shaped how Emily Zhang teaches system design. Every link opens free.
Open the list→PM Reading Stack
Aisha's working list — Inspired, Continuous Discovery, the Lenny posts that actually held up.
Open the list→Cloud + DevOps
AWS whitepapers, the Terraform book, and the SRE handbook. Liam's curation.
Open the list→UX Research Foundations
Methods, classic studies, and the writing on practice that Maya assigns first.
Open the list→Library FAQ
Find what you need?
If a topic isn't covered, ask in our Discord — instructors curate new lists once they have three good requests.