Computational techniques for large-scale data

Utbildningsfakta

Kod: DIT066

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.

Behörighet

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.

Utbildningstillfällen

Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.

• Computational techniques for large-scale data

  University of Gothenburg

  GÖTEBORG

  Startdatum: 22 mars 2027

  Slutdatum: 6 juni 2027

  Studietakt: 50 %