Google · Course
Managing ML Projects
Managing ML Projects is a Google for Developers course on managing a machine learning project from idea to production-ready implementation, covering the phases, the roles on an ML team, working with stakeholders, success metrics and responsible AI.
Who it suits
- Product managers, team leads and engineers who run or sponsor ML projects.
- People who already know basic machine learning and have decided ML fits their problem.
What it covers
- The ML development phases and the roles and skills typically found on ML teams.
- Planning and management strategies, and establishing success metrics.
- Responsible AI practices in a project.
- Common principles and key differences when managing generative AI projects.
Before you start
- A basic understanding of machine learning.
- You have already determined that ML is the right solution for your problem.
Common questions about Managing ML Projects
- How long does it take?
- Google estimates about 90 minutes.
- Does it cover generative AI?
- It focuses on traditional ML models, with insights on managing generative AI projects.
- Is it free to reuse?
- Google says the content is licensed under Creative Commons Attribution 4.0, and code samples under Apache 2.0.
More like this
Keep learning on Infrato
- Path: AI for product managers
- Path: AI for data analysts
- More from Google: all Google listings in the directory
- Explore all AI courses
Where this comes from
Written from Google’s own pages, read on 2026-10-14. Content, prices and availability change, so the provider’s page is the source. We are not affiliated with Google and this is not an endorsement.