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The course focuses on challenges and concepts related to software engineering aspects of systems based on artificial intelligence. The course offers knowledge and support for students to be able to implement AI systems successfully, and covers the life cycle of AI systems from the perspective of software engineering in terms of requirements management, design, implementation, testing, and maintenance. The course also explains implementation problems in the workflow of an ML system in production, including continuous integration (CI) and continuous delivery (CD) for ML models, and covers issues related to machine learning operations (MLOps), suitable ways of creating integrated systems, and the architectural considerations required for roll-out systems, including quality assurance (QA) of MLOps for those systems.

Progressive specialisation: A1F (has second‐cycle course/s as entry requirements)

Education level: Master's level

Selection:

Selection is usually based on your grade point average from upper secondary school or the number of credit points from previous university studies, or both.

This course is included in the following programme

• Master of Science in Computer Engineering (studied during year 5)
• Master in Computer Science (studied during year 2)
• Master´s Programme in Intelligent Software Systems (studied during year 2)