AI Engineering

Education facts

Code: DVAE26

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.

Entry requirements

Upper secondary level English 6 or English level 2, or equivalent. Foundations of AI and optimisation methods (7.5 credits) and Distributed systems and cloud computing (7.5 credits). Equivalence assessment may be made.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• AI Engineering

  Karlstad University

  Karlstad

  Start date: 9 November 2026

  End date: 17 January 2027

  Pace of study: 50 %