Scientific Computing for Data Analysis
Course, Bachelor's level, 1TD352
Expand the information below to show details on how to apply and entry requirements.
Spring 2026 Spring 2026, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 19 January 2026–22 March 2026
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
- 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 10,833
- Total tuition fee: SEK 10,833
- Application deadline
- 15 October 2025
- Application code
- UU-62032
Admitted or on the waiting list?
- Registration period
- 5 January 2026–25 January 2026
- Information on registration from the department
Spring 2026 Spring 2026, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 19 January 2026–22 March 2026
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
Admitted or on the waiting list?
- Registration period
- 5 January 2026–25 January 2026
- Information on registration from the department
Spring 2026 Spring 2026, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 23 March 2026–7 June 2026
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
- 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 10,833
- Total tuition fee: SEK 10,833
- Application deadline
- 15 October 2025
- Application code
- UU-62042
Admitted or on the waiting list?
- Registration period
- 9 March 2026–29 March 2026
- Information on registration from the department
Spring 2026 Spring 2026, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 23 March 2026–7 June 2026
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
Admitted or on the waiting list?
- Registration period
- 9 March 2026–29 March 2026
- Information on registration from the department
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
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
- Application deadline
- 15 April 2026
- Application code
- UU-12032
Admitted or on the waiting list?
- Registration period
- 27 July 2026–6 September 2026
- Information on registration from the department
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
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
Admitted or on the waiting list?
- Registration period
- 27 July 2026–6 September 2026
- Information on registration from the department
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 2027–21 March 2027
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
- Application deadline
- 15 October 2026
- Application code
- UU-62032
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 2027–21 March 2027
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
Admitted or on the waiting list?
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
- 22 March 2027–6 June 2027
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
- Application deadline
- 15 October 2026
- Application code
- UU-62033
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
- 22 March 2027–6 June 2027
- Language of instruction
- English
- Entry requirements
-
60 credits including Algebra and Geometry/Linear Algebra and Geometry I/Linear algebra I. Participation in a programming course in Python (for example Computer Programming I). Participation in one of the courses Introduction to Scientific Computing, Scientific Computing I, or Statistical Machine Learning. Participation in Probability and Statistics or Mathematical Statistics KF. Participation in Linear Algebra II/Linear Algebra for Data Analysis/Geometry and Calculus II.
Admitted or on the waiting list?
About the course
This course focuses on handling large amounts of data and is divided into three different blocks. The first block deals with stochastic simulations, the second with regression analysis and least squares methods and the third with eigenvalue problems, singular value decomposition and principal component analysis. In the field of data analysis and machine learning, many algorithms and applications are based on the methods covered in this course. We study the computational methods used when working practically with data analysis of large amounts of data.