MLOps Fundamentals - LTAT.02.038
The course introduces the fundamental concepts and practices of Machine Learning Operations (MLOps). It covers the complete ML lifecycle, including data management, experiment tracking, model packaging, deployment, monitoring, and workflow automation. Students learn how to build reproducible, scalable, and maintainable ML systems using modern MLOps tools and principles.
All practical sessions in the subject are done in person in the classroom but everyone is allowed to finish it at home and submit.
Time and place
Lectures (Asad munir)
- Thursday 14.15-16.00 in room 1008
Practice Sessions (Asad Munir)
- Fridays 08.15-10.00 in room 2006. NB! There will be no practical session for the first week of study (19.02.2026 and 20.02.2026) and there is no classes and activity for first week (12.02.2026 and 13.02.2026) so First practical on 27.02 in room 1008 - bring your own computer!
Evaluation
- Weekly Practices Performance-based continuous assessment evaluation of weekly lab submissions.
- Reading Assignment Evaluation based on participation in guest lectures, reading assignments, and in-class discussions.
- Project Performance and presentation — students work in teams to design and implement an end-to-end MLOps pipeline integrating data management, model tracking, deployment, and monitoring
Contact
- Asad Munir (asad.munir@ut.ee)