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University of Gothenburg
Statistical Methods for Data Science
<p>The course gives an introduction to the theory of probability and statistics, data analysis using descriptive statistics and data visualization, and applications of probabilistic modeling in data science.</p> <p>In the course, the following broad areas will be covered:</p> <ul> <li>data analysis including desc…
- Higher education
- Information unavailable
- 4 November 2024
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>The course gives an introduction to the theory of probability and statistics, data analysis using descriptive statistics and data visualization, and applications of probabilistic modeling in data science.</p> <p>In the course, the following broad areas will be covered:</p> <ul> <li>data analysis including descriptive statistics and data visualization</li> <li>probability theory including basic probability calculations, random variables</li> <li>distributions statistical methods including point and interval estimates</li> <li>hypothesis testing, regression probabilistic models in data science applications, for instance, Naive Bayes classifiers and topic models for text or Hidden Markov Models for sequences</li> </ul>
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Entry requirements
To be eligible to the course, the student should have a Bachelor’s degree in any subject, or have successfully completed 90 credits of studies in computer science, software engineering, or equivalent. Specifically, the course requires the following: at least 15 credits of successfully completed courses in programming, one of the courses DIT852 Introduction to Data Science or equivalent, or DIT856 Applied Mathematical Thinking or equivalent. Alternatively at least 15 credits of mathematics or mathematical statistics. Applicants must prove knowledge of English: English 6/English B or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.
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
- 2024-11-04
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.dit863.18675.20242
- Last checked
- 2026-09-23T10:36:42.164498+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.gu.dit863.18675.20242
- Offering identity in the source
- e.uoh.gu.dit863.18675.20242
- Education-form source code
- HS
- Education code in the source
- DIT863
- Change time according to the source
- 2024-10-25T12:27:42
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.