Building AI Products
This course provides a practical playbook for creating products powered by artificial intelligence and machine learning, including large language models (LLMs), agents, and multi-agent systems. Students explore the full product lifecycle, with particular emphasis on data and evaluations. Designed for anyone interested in AI products, the course welcomes aspiring product managers, startup founders, product attorneys, and students pursuing other roles. Diverse perspectives are valued, and no prior experience or expertise in machine learning, AI, LLMs, or agents is required. Any Cornell Tech student can succeed in the course. Some coding is involved, but students work in groups and are encouraged to use AI-assisted coding. The course offers an accessible foundation for contributing to AI product development across a range of professional paths.
Topics
- Demonstrate fundamental understanding of the baseline process for productizing machine learning.
- Demonstrate the ability to critically adapt or revise the baseline process for productizing machine learning when applying it to a new target problem.
- Demonstrate fundamental understanding of common industry tools and processes for productizing machine learning.
- Demonstrate ability to thoughtfully map readings, lectures, and in-class comments and questions from classmates onto a new target problem chosen by student.
Official roster learning outcomes
Prerequisites & course information
TECH 5900.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Productizing Machine Learning · 1.0 · Graduate