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Applied Data Science masterprogram

Avancerad nivå | 120 hp
HT 2020
100% Dag
Kommentar: Observera att undervisningsspråk har ändrats gentemot vad som tidigare angivits. Kursen kommer att ges på engelska.

Om programmet

Data Science is concerned with extracting meaning from large volumes of data. It is a field that has grown rapidly in recent years as a result of the increasing availability of large data sets, and the opportunities and challenges that these present. Central topics within Data Science include data mining, machine learning, databases, and the application of data science methods in natural sciences, life sciences, business, humanities and social sciences, as well as in industry and society.

Data Science is having a big impact on industry. For some companies, being able to handle and analyse massive data sets is central to their business model. Even for other companies, being able to extract information from data (e.g. data about customers) can offer crucial competitive advantages. People with knowledge and skills in Data Science are therefore in high demand, in Gothenburg and internationally. Similarly, within scientific research, data-intensive scientific discovery is increasingly important in many areas, and researchers need to be able to handle and analyse massive data sets. Thus, providing training in the management and analysis of large-scale data is important in preparing students for further study and research within higher education, research institutes and industry.

The Master's programme in Applied Data Science is designed to be accessible to students with a wide range of Bachelor's degrees, and a Master's level education in Applied Data Science will be of benefit to students with backgrounds in many different areas who recognise that being able to work effectively with large data sets will be important in their future careers. Some previous programming experience is required, and the programme builds on this. The programme gives students an overview of the techniques and technologies that are relevant to Data Science, an appreciation of when and how these can be used, and practical skills in their application.

This two-year programme includes the following compulsory courses that provide a core within Data Science:

  • Introduction to Data Science (7.5 credits)
  • Applied Mathematical Thinking (7.5 credits)
  • Statistical Methods Data Science (7.5 credits)
  • Applied Machine Learning (7.5 credits)
  • Techniques for Large-scale Data (7.5 credits)
  • Research Methods for Data Science (7,5 credits)
  • Master’s Thesis in Data Science (30 credits)

Applied Data Science is multi-disciplinary by nature, and the programme is designed to allow space for students to create their own profiles by choosing optional courses. Students can choose courses in areas where Data Science methods can be applied, or courses in technical areas that feature techniques and technologies that complement those introduced in the programme's compulsory courses. Students are particularly encouraged to supplement the compulsory courses that provide a core in Data Science with optional second-cycle courses in the area of their first degree.

Mer information om programmet

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Behörighet och urval

Förkunskapskrav: Kandidatexamen om 180 högskolepoäng (hp) inklusive ett examensarbete (självständigt arbete) om minst 15 hp eller motsvarande. Minst 15 hp programmering eller motsvarande. Engelska 6/ Engelska B eller motsvarande.

Urval: The selection is based on (i) a Personal Letter, (ii) grades from previous higher education. The Personal Letter should explain clearly the motivation for choosing this programme and this institution. The letter should introduce the applicant both personally and professionally, and discuss the relevance of the applicant's Bachelor's degree subject to Applied Data Science. The document must be entirely unique, i.e., it must not contain any part which is copied from any other source (with the exception of explicit quotations). Applications will be considered only if a Personal Letter is included.




Institutionen för data- och informationsteknik
41296 Göteborg

Besöksadress: Rännvägen 6 B

Sidansvarig: Pontus Sundén
Sidan uppdaterades: 2020-02-18 14:41

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Sidansvarig: Pontus Sundén|Sidan uppdaterades: 2019-01-11

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