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Uppsala University
Scientific Computing for Data Analysis
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…
- Higher education
- Information unavailable
- 18 January 2027
- Uppsala
- Information unavailable
- 33 %
Overview
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.
Admission scores
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.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2027-01-18
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.uu.1td352.62032.20271
- Last checked
- 2026-09-23T10:39:41.205927+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
Programme content
Study structure
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- Programme or course starts
- Programme or course ends
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.uu.1td352.62032.20271
- Offering identity in the source
- e.uoh.uu.1td352.62032.20271
- Education-form source code
- HS
- Education code in the source
- 1TD352
- Change time according to the source
- 2026-09-10T10:12:46
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.