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Research Methods for Intelligent Systems 7,5 Credits

Course Contents

The course comprises of lectures and seminars. The lectures broadly cover the theoretical foundations of typical research approaches in artificial intelligence and related areas as well as common research methods and ways of reporting research findings. The seminars cover academic communication, state-of-the-art development in artificial intelligence from a scientific perspective, and open research questions and challenges.

The course includes the following elements:
- Information retrieval and literature surveys
- Qualitative and quantitative approaches to research
- Computer science as a scientific paradigm
- Research methods in computer science
- Basic and applied research in artificial intelligence
- Ethical considerations
- Assessment of scientific quality

Prerequisites

Passed courses at least 90 credits within the major subject Informatics, and completed course Machine Learning, 7,5 credits or equivalent. Proof of English proficiency is required.

Level of Education: Master
Course code/Ladok code: TRIS20
The course is conducted at: School of EngineeringLast modified 2020-10-26 10:27:37

Content updated 2020-08-25