Over the past several years I put together a set of lecture notes for teaching bioinformatics, pairing classic Python/BioPython methods with AI-assisted workflows so students could see both approaches side by side.
I’ve cleaned them up and organized them into a free 14-chapter book: Bioinformatics with AI: A Modern Introduction. It moves from the basics (the central dogma, biological data, Python fundamentals) through sequence alignment, gene expression, and protein structure, into genome analysis, metagenomics, single-cell data, and using LLMs for bioinformatics reasoning, ending with pipeline-building and capstone projects.
Figured these notes might be useful to others teaching or learning this material, so I’m posting the whole thing. Free, no login. Published through Envoi Publishing (ISBN 978-1-890222-12-3).