Natural Computation Methods for Machine Learning
Course, Master's level, 1DL073
Spring 2024 Spring 2024, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 15 January 2024–2 June 2024
- 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.
- Selection
-
Higher education credits in science and engineering (maximum 240 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- First tuition fee instalment: SEK 24,167
- Total tuition fee: SEK 24,167
- Application deadline
- 16 October 2023
- Application code
- UU-61011
Admitted or on the waiting list?
- Registration period
- 15 December 2023–22 January 2024
- Information on registration from the department
Spring 2024 Spring 2024, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 15 January 2024–2 June 2024
- 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?
- Registration period
- 15 December 2023–22 January 2024
- Information on registration from the department
Spring 2025 Spring 2025, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 20 January 2025–8 June 2025
- 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.
- Selection
-
Higher education credits in science and engineering (maximum 240 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- First tuition fee instalment: SEK 24,167
- Total tuition fee: SEK 24,167
- Application deadline
- 15 October 2024
- Application code
- UU-61011
Admitted or on the waiting list?
- Registration period
- 20 December 2024–27 January 2025
- Information on registration from the department
Spring 2025 Spring 2025, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 20 January 2025–8 June 2025
- 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?
- Registration period
- 20 December 2024–27 January 2025
- Information on registration from the department
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.