MLOps (5 cr)
Code: MS00CN45-3001
General information
Enrollment
02.12.2023 - 15.01.2024
Timing
15.01.2024 - 30.04.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Engineering and Business
Teaching languages
- Finnish
- English
Degree programmes
- Master of Engineering, Data Engineering and AI
- Master of Business Administration, Data Engineering and AI
Teachers
- Tommi Tuomola
Groups
-
YDATIS23
-
YDATTS23
- 15.01.2024 08:30 - 11:45, Machine Learning Engineering for Production MS00CN45-3001
- 16.01.2024 12:30 - 16:00, MLOps MS00CN45-3001
- 13.02.2024 12:30 - 16:00, MLOps MS00CN45-3001
- 12.03.2024 12:30 - 16:00, MLOps MS00CN45-3001
- 16.04.2024 12:30 - 16:00, MLOps MS00CN45-3001
Objective
After completing the course, the students can
- describe and understand how MLOps projects operate
Content
- Process and tools for Machine Learning Engineering for Production (MLOps)
Materials
Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.
Itslearning and contact classes are the main communication channels used on this course.
The student is required to have a computer capable of running a simple Ubuntu virtual machine.
Teaching methods
Contact learning, practical assignments, independent study
Student workload
Contact hours 16 h
Inpendent studying 119h, including:
- Studying the course material
- Completing assignments
- Project
Content scheduling
After completing the course, the students can
- describe and understand how MLOps projects operate
Process and tools for Machine Learning Engineering for Production (MLOps)
Scheduling:Chosen topics from MLops, Dataops and Devops for artificial intelligence and data engineering students.
Evaluation scale
H-5
Assessment methods and criteria
Assignments returned throughout the course
Small project at the end of the course