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University of Gothenburg
Computational techniques for large-scale data
The advent of big-data has led to the development of new programming paradigms, in particular for parallel systems allowing the computation with big data on redundant clusters of commodity computers. This course provides an introduction to different programming paradigms, e.g. MapReduce and extensions, which facilit…
- Higher education
- Information unavailable
- 22 March 2027
- GÖTEBORG
- Information unavailable
- 50 %
Overview
The advent of big-data has led to the development of new programming paradigms, in particular for parallel systems allowing the computation with big data on redundant clusters of commodity computers. This course provides an introduction to different programming paradigms, e.g. MapReduce and extensions, which facilitate computations with Terabytes of data. It also demonstrates that for specific tasks algorithms and data structures can provide highly efficient alternatives.
Admission scores
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, at least 15 credits of successfully completed courses in programming, or equivalent are required. The student needs to have successfully completed a course in probability theory or statistics. Applicants must prove knowledge of English: English 6/English level 2 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
- 2027-03-22
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.dit066.86060.20271
- 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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- 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.gu.dit066.86060.20271
- Offering identity in the source
- e.uoh.gu.dit066.86060.20271
- Education-form source code
- HS
- Education code in the source
- DIT066
- Change time according to the source
- 2026-08-20T07:42:37
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.