Natural Computation Methods for Machine Learning
10 credits
Course, Master's level, 1DL073
Expand the information below to show details on how to apply and entry requirements.
Spring 2027 Spring 2027, 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
- 18 January 2027–6 June 2027
- Language of instruction
- English
- Entry requirements
-
120 credits including 15 credits in mathematics and 60 credits in computer science/information systems, including 20 credits in programming/algorithms/data structures. Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Application deadline
- 15 October 2026
- Application code
- UU-61011
Admitted or on the waiting list?
Spring 2027 Spring 2027, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 18 January 2027–6 June 2027
- Language of instruction
- English
- Entry requirements
-
120 credits including 15 credits in mathematics and 60 credits in computer science/information systems, including 20 credits in programming/algorithms/data structures. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
About the course
After the course you should be able to:
- set up and solve typical natural computation problems
- by implementation or with simulation tools, determine the applicability of different learning methods to different types of learning problems, i.e. know the strengths and weaknesses of the method
- set a good representation of the data
- recognise the typical effects of bad choices and determine how to improve the results
- describe how and why machine learning and natural computation methods (such as deep learning and genetic algorithms) work.
Reading list
No reading list found.