Advanced course for PhD students
- AI track: elective
- AS track: elective
- Joint curriculum: advanced
Time: Given odd years, Spring- First time spring 2026
Teachers: Sofia Ouhbi (UU), Per-Olov Östberg (UmU), Mattias Tiger (LiU)
Examiner: Per-Olov Östberg (UmU)
The course is designed for PhD students from diverse backgrounds. The course requires solid programming experience in a high-level language.
After completing the course, the students will have theoretical and practical knowledge about software engineering and AI. Specifically, students should be able to:
-Explain key software engineering challenges for AI-enabled software systems.
-Identify relevant quality attributes for AI-enabled software systems in diverse contextsof use.
-Analyze trade-offs among quality attributes of AI-enabled software systems.
-Outline performance trade-offs for modularized and distributed software systems
-Describe techniques for assessing and controlling system performance in runtime
-Evaluate architecture and component-level techniques for system scalability
-Describe MLOps practices and AI harness architectures for managing and deployingAI models in production.
-Compare automated optimization approaches for AI systems development.
-Analyze quality assurance challenges in AI-assisted software engineering, includingtesting strategies for AI-enabled software systems.
The course includes three 2-day meetings with intense teaching on-site, typically a mixture of lectures and exercises.
Module 1 is held in Uppsala and consists of lectures, active learning exercises, and a seminar in which students present and discuss their results.
Module 2 is held in Umeå and consists of lectures, practical exercises, and group discussions.
Module 3 is held in Linköping and consists of lectures, practical labs and active learning
Participants in the course will be assessed using hand-in assignments, practical assignments, and oral presentations. To pass each individual module the student must receive a passing grade in the module’s assignments and have actively participated in the in-person meetings. To pass the course the student must pass all modules.
A re-examination is prepared about 6 months after the course covering completion of missing parts.