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Lund University
Statistics: Programming for Data Science
<p>Want to improve your programming skills and learn how code is used in statistics and data science? This course gives you hands-on experience with R and Python - two of the most widely used languages in modern data analysis.</p><p>This course introduces you to modern statistical programming in data science. You’ll…
- Higher education
- Information unavailable
- 31 August 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>Want to improve your programming skills and learn how code is used in statistics and data science? This course gives you hands-on experience with R and Python - two of the most widely used languages in modern data analysis.</p><p>This course introduces you to modern statistical programming in data science. You’ll learn how to use R and Python to solve practical problems and implement key statistical methods. Topics include:</p><ul><li>statistical packages and modules in R and Python</li><li>data handling using data frames, arrays and matrices</li><li>random number generation and simulation</li><li>Monte Carlo methods for integration, inference and variance reduction</li><li>bootstrap and other resampling techniques</li><li>Bayesian analysis and MCMC methods</li><li>numerical methods and optimisation.</li></ul>
Admission scores
Entry requirements
90 credits in Statistics, or a total of 90 credits i Mathematics, Programming, Mathematical Statistics and Statistics, of which at least 45 credits in Statistics or Mathematical Statistics, or the equivalent.
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.lu.stan48.e1063.20262
- Last checked
- 2026-09-23T10:38:33.477975+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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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.lu.stan48.e1063.20262
- Offering identity in the source
- e.uoh.lu.stan48.e1063.20262
- Education-form source code
- HS
- Education code in the source
- STAN48
- Change time according to the source
- 2026-02-10T09:21:03
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.