MLOps Zoomcamp

DataTalks.Club organizes MLOps into a nine-week curriculum with homework and a final project. Experiment tracking and model management lead into pipelines, deployment and monitoring. The public materials remain available for self-paced study, while the provider states that no live cohort is planned for 2026.

What you will learn

• Track experiments and manage model artifacts.
• Organize pipelines and deploy model services.
• Monitor and review an end-to-end ML project.

Who this suits

Learners who know Python, Docker basics and the ML workflow, with about a year of programming experience as recommended by the provider.

Before you enroll

Check the cloud-account, software and lab requirements before enrolling. Hosting, storage and GPU resources can incur separate charges. Use permitted sample data, record dependencies and test a rollback or failed pipeline step alongside the successful deployment.

Videos, materials and homework are free and open source. Self-paced homework is not scored and does not provide the live-cohort certificate. Cloud resources used for exercises can have separate charges.

Put it into practice

Build a small permitted-data project and document its tracking, deployment and monitoring steps so another learner can reproduce the system.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

Level is an editorial estimate based on the published prerequisites. The duration filter reflects the nine-week curriculum rather than video time alone.

View the curriculum and current access options at DataTalks.Club.

How YellowCourse describes and checks learning resources.