Applied Data Science Master's Programme - University of Gothenburg Till startsida
Sitemap
To content Read more about how we use cookies on gu.se

Applied Data Science Master's Programme

Master's programme | 120 credits
Autumn 2020
100% Day
Göteborg
INSTRUCTION LANGUAGE: English
1 Closed GU-68699 2 Closed GU-18699
1) Anyone can apply
2) Only EU/EEA citizens and students with approved residence permit in Sweden can apply

About the Programme

Big Data is taking centre stage in all areas—business and industry, public policy, the life sciences, natural sciences, humanities, and social sciences. People with knowledge of how to process and analyse large amounts of data are becoming increasingly sought after. This full-time on-campus programme consists of courses in applied data science and related subjects. The courses are progressively arranged so that they, within the framework of learning outcomes, contribute separately and jointly to develop your skills and abilities in the field.

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 they 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.

Training in the management and analysis of large-scale data

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 (for example, data about customers) can offer crucial competitive advantages. People with knowledge and skills in data science are therefore in high demand, in Gothenburg, in Sweden, 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.

Welcoming students with backgrounds in many different areas

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 education in applied data science will be of benefit to students with backgrounds in many different areas who recognize 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 they can be used, and practical skills for their application.

Structure and content

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

  • Introduction to Data Science
  • Python for data scientists
  • Applied Mathematical Thinking
  • Statistical Methods for Data Science
  • Applied Machine Learning
  • Techniques for Large-Scale Data
  • Research Methods for Data Science
  • Master’s Thesis in Data Science

Applied data science is multidisciplinary by nature, and the programme is designed to allow space for you to create your own profile by choosing optional courses. You 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 mandatory courses. You are particularly encouraged to supplement the mandatory courses that provide a core in data science with optional second-cycle courses in the area of your bachelor’s degree.

After graduation

Graduates of the programme will receive the degree Master of Science in Applied Data Science.

With this programme you will obtain advanced knowledge in applied data science, and once the programme is completed you will be able to either pursue a specialist career in industry or move ahead in academic research.

You will be prepared to work with Big Data in your future career. You will learn about different data science methods, their applicability, and advantages and disadvantages of different techniques. You will have the knowledge and skills necessary to respond to the challenges and opportunities that emerge as massive data sets become increasingly available.

More information

https://www.gu.se/studera/hi...

Show more

Requirements and Selection

Requirements: A Bachelor s degree of 180 credits including an independent project (degree project) of at least 15 credits or equivalent. At least 15 credits from programming or equivalent. Applicants must prove their knowledge of English: English 6/English B from Swedish Upper Secondary School or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.

Selection: 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.

Tuition Fee

Application fee: 900 SEK
Full programme cost: 286 000 SEK
First payment: 71 500 SEK

EU/EEA citizens, Swedish residence permit holders and exchange students do not pay fees. More information on: http://www.universityadmissions.se

Study Guidance

E-post: svl@cse.gu.se

Department

Department of Computer Science and Engineering
41296 Göteborg

Visiting address: Rännvägen 6 B

Page Manager: Pontus Sundén
Last update: 2/18/2020 2:41 PM

Tell a friend about this page
Print version

Page Manager: Pontus Sundén|Last update: 10/25/2018
Share:

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?