Statistical Machine Learning

5 credits

Course, Master's level, 1RT700

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 November 2026–17 January 2027
Language of instruction
English
Entry requirements

120 credits including Probability and Statistics, Linear Algebra II, Single Variable Calculus and a course in introductory programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Application deadline
15 April 2026
Application code
UU-11808

Admitted or on the waiting list?

Registration period
19 October 2026–8 November 2026
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 November 2026–17 January 2027
Language of instruction
English
Entry requirements

120 credits including Probability and Statistics, Linear Algebra II, Single Variable Calculus and a course in introductory programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
19 October 2026–8 November 2026
Information on registration from the department

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
18 January 2027–21 March 2027
Language of instruction
English
Entry requirements

120 credits including Probability and Statistics, Linear Algebra II, Single Variable Calculus and a course in introductory programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Application deadline
15 October 2026
Application code
UU-61812

Admitted or on the waiting list?

Information on registration from the department

About the course

This is an introductory course in statistical machine learning, with a focus on classification and regression. Fundamental methods are taught and applied to real data.