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Halmstad University
Principles and Techniques for Data Science
- Introduction: different components of the data science life cycle - Classification of different methods for data processing: retrieval, structuring - Cleaning, transformation, etc., and description of various data types - Introduction of different paradigms for exploratory data analysis, such as statistics - Analy…
- Higher education
- Information unavailable
- 31 August 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
- Introduction: different components of the data science life cycle - Classification of different methods for data processing: retrieval, structuring - Cleaning, transformation, etc., and description of various data types - Introduction of different paradigms for exploratory data analysis, such as statistics - Analysis, scores, ranking, hypothesis testing, and data visualization - Overview of data mining techniques for understanding trends, outliers, and patterns from large amounts of data - Presentation of various methods for predictive modeling - Introduction of data science tools: programming, computing environments, and big data infrastructures - Presentation of data ethics: privacy, security, fairness, bias, and interoperability - Providing guidance on how to do data science project
Admission scores
Entry requirements
The courses Introduction to Data Science 15 credits and Linear Algebra for Data Science 7.5 credits. English 6 or English level 2. Exemption of the requirement in Swedish is granted for those with foreign grades.
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
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.hh.ds4007.x3015.20262
- Last checked
- 2026-09-23T10:37:30.869721+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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Previous upper-secondary schools and programmes
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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.hh.ds4007.x3015.20262
- Offering identity in the source
- e.uoh.hh.ds4007.x3015.20262
- Education-form source code
- HS
- Education code in the source
- DS4007
- Change time according to the source
- 2026-02-22T13:18:36
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.