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State-of-the-Art in AI Research 7,5 Credits

Course Contents

The course goes into depth in terms of selected topics and methods within AI, machine learning and their applications. Examples may include areas, such as computational intelligence algorithms in search, optimization and classification, natural language processing and FAT (fairness, accountability, transparency) aspects. Examples of relevant applications could include robotics, music, health and medicine.

The course is an advanced course in state-of-the-art research in the field of AI engineering. The course covers advanced research and recent trends in the field, alternating theory with practice. After completing the course, the student shall have acquired a broad knowledge of state-of-the-art research in the field of AI engineering. Specifically, the student should be familiar with state-of-the-art research and trends in the field, advantages and challenges of AI, areas in need of further research, and be able to evaluate and criticize a subset of the research topics covered.

The course includes the following elements:
- Introduction to recent trends the field, alternating theory and practice
- Introduction to theory and methods within AI
- Introduction to challenges of AI
- Introduction to the advantage of AI


Passed courses at least 90 credits within the major subject Computer Engineering, Electrical Engineering (with relevant courses in Computer Engineering), or equivalent, or passed courses at least 150 credits from the programme Computer Science and Engineering, and completed course Data Science Programming, 7,5 credits or equivalent. Proof of English proficiency is required.

Level of Education: Master
Course code/Ladok code: TSFS22
The course is conducted at: School of EngineeringLast modified 2021-11-04 14:59:19