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Algorithms and Systems for Autonomous Vehicles

The course provides an in-depth introduction to autonomous vehicles where both Artificial Intelligence (AI) algorithms and their system aspects are studied. Autonomous vehicles can be about cars, trucks, drones, or different types of special vehicles, such as mobile robots. The development of autonomous vehicles can lead to changes in several industries in the not so distant future. An autonomous vehicle is equipped with built-in processors and sensors that can detect the environment, perform sensor fusion for decision making, and have continuous control and steering.

Course Details

• Type: Course, second cycle
• Study pace: Half speed
• Study location: Varied
• Type of studies: Distance only (no required meetings)

About the Course

The course consists of both theoretical and experimental elements, and is closely related to current research and development. The topics covered include:

• Key concepts of the perception-planning-control pipeline for autonomous driving (AD)
• Key concepts of machine learning (ML), especially reinforcement learning (RL), and deep reinforcement learning (DRL)
• Hands-on exercises with one of the popular open-source ML frameworks such as Tensorflow or PyTorch
• Training, deployment, and validation of ML-based autonomous driving algorithms in a simulation environment

Eligibility and Selection

• Admission to the course requires 90 credits of previous studies including courses in the field of Artificial Intelligence or Machine Learning of at least 7.5 credits.
• Selection is based on academic credits.

Application and Tuition Fees

• As a citizen of a country outside the European Union (EU), the European Economic Area (EEA), or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.
• Application fee: SEK 900
• Tuition fee, first instalment: SEK 19,038
• Total fee: SEK 19,038

Course Schedule

• Starts: 3 November 2025
• Ends: 18 January 2026
• Number of credits: 7.5 credits
• Type of studies: Web-based (online)
• Mandatory meetings: No mandatory meetings
• Other meetings: None
• Study pace: 50%
• Teaching hours: Mixed
• Study location: Varied
• Language: English
• Application code: UMU-54206

Provided by

The course is given by Applied Physics and Electronics.