Artificial Intelligence
Course, Master's level, 1DL340
Expand the information below to show details on how to apply and entry requirements.
Autumn 2026 Autumn 2026, Uppsala, 33%, On-campus, English Only available as part of a programme
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 31 August 2026–1 November 2026
- Language of instruction
- English
- Entry requirements
-
120 credits including 15 credits in mathematics and 20 credits in computer science, including a second course in programming. Alternatively 45 credits in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Application deadline
- 15 April 2026
- Application code
- UU-11010
Admitted or on the waiting list?
Autumn 2026 Autumn 2026, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 31 August 2026–1 November 2026
- Language of instruction
- English
- Entry requirements
-
120 credits including 15 credits in mathematics and 20 credits in computer science, including a second course in programming. Alternatively 45 credits in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
About the course
"What is intelligence"? is a deep philosophical question. The topic of this course is more practical: how can we make computers perform tasks that - up to now - are difficult for computers? Tasks that require an "intelligent" approach, because computing power alone is not enough.
Even before the first computer was built, it was thought of as possibly intelligent. Obviously, computers would talk - a three-year-old child can talk. Playing chess, now that would be intelligent! A computer has since beaten the world Master in chess and fulfilled many other promises. This course is about the successes of artificial intelligence (AI). However, knowing how they work takes away part of the magic, or "intelligence".
Artificial intelligence requires knowledge representation and reasoning. There are many different approaches. Expert systems knowledge consists of facts and rules, clearly visible and separate from reasoning. In neural networks, knowledge is implicit and entangled in the reasoning process. Reasoning is not a straightforward computation. It is a search: making guesses and trying different solutions. Heuristic search is at the heart of AI: methods that try to make "intelligent" guesses.
Nowadays many applications contain AI, often in disguise. Google finds relevant search results. You can talk to a computer and book a railway ticket. The monsters in computer games come right at you. This diversity of applications is reflected in the topics of the course: expert systems, learning, planning, playing games like chess, and so on.