17-645 Machine Learning in Production

12 units, Carnegie Mellon University

This course prepares future AI engineers, software engineers, data scientists, and product managers to build and operate production-grade software applications powered by machine learning, going from models and demos to production. The focus is on turning ML models, LLMs, and AI agents into reliable, scalable, and maintainable software systems that deliver real value to users. The course covers the full application lifecycle: requirements, construction, testing, deployment, and maintenance, with extensive attention to MLOps and responsible AI, including safety, security, fairness, and explainability. It is designed both for software engineers seeking to understand the challenges of working with AI components and for data scientists looking to bridge the gap from prototype to production, supporting communication and collaboration across both roles. LECTURE 2 section A for CMU Africa Students only

Prerequisites: none listed

Offered: Spring 2027, Fall 2026, Spring 2026, Fall 2025

Courseweave needs JavaScript to show sections, workloads and planning tools.