From creating new medicines to unlocking the mysteries of proteins, AI is transforming biology. This course introduces students to the algorithms behind generative AI and shows how they can be applied to biological design. You’ll begin with the core concepts of machine learning, then advance to modern AI approaches that power today’s breakthroughs. Along the way, you’ll code in Python, collaborate on group projects, and share your work on platforms used by AI researchers worldwide. By the end of the course, you’ll be prepared to think like a researcher at the exciting intersection of AI and biology.
Eligible students should have one year of Calculus and be proficient in coding in the language of Python. Differential Equations and Linear Algebra are encouraged. Biology coursework is optional.
Instructor: Dr. Pranam Chatterjee
Dr. Chatterjee is an Assistant Professor of Bioengineering and Computer and Information Science at the University of Pennsylvania. His laboratory, the Programmable Biology Group, develops new methods for de novo protein and peptide design, integrating new algorithmic theory for generative sequence modeling with translational in vitro and in vivo experimental platforms. Specifically, the lab uses these tools for diverse protein modulation, genome editing, and cell engineering applications, with particular focus on developing therapeutics for rare pediatric neurodegenerative diseases and cancers and molecules for bioremediation. He has co-founded four companies, Gameto Inc., UbiquiTx Inc., AtomBioworks Inc., and Recognition Bio, Inc., which are building upon my foundational research to develop novel protein-based fertility solutions, cancer therapeutics, and mRNA medicines.
This course is new for the 2026 year and the syllabus is still in the development phase. A comprehensive syllabus will become available in the coming months.
Glasp, citing a TEDxMIT talk by Geoff von Maltzahn
Bill Gates, 2024
