AIX7864 MACHINE LEARNING ENGINEERING AND OPERATIONS
| Course Code: |
8877864 |
| METU Credit (Theoretical-Laboratory hours/week): |
3(2-2) |
| ECTS Credit: |
8.0 |
| Department: |
Artificial Intelligence Engineering |
| Language of Instruction: |
English |
| Level of Study: |
Graduate |
| Course Coordinator: |
|
| Offered Semester: |
Fall and Spring Semesters. |
Course Content
This course focuses on engineering and operating production-ready machine learning systems. Students learn how to transform research code into reproducible, maintainable, and scalable ML solutions through data and model versioning, experiment tracking, automation, deployment, and CI/CD.
The course covers the full ML lifecycle using standard process models (e.g., CRISP-DM), collaborative Git workflows, and best practices for treating data as a fýrst-class asset. Through hands-on practice, students build automated training pipelines and deploy inference services, while analyzing trade-offs between online, offline, and hybrid de 10 ment strateies
