Applied Data Science masterprogramGöteborgs universitet
|Applied Data Science masterprogram||GU-18699||HT2017||x|
Urvalsgrupperna anges med förkortningar. Förkortningarna kan variera mellan olika terminer och olika högskolor. De vanligaste är:
|BI||Gymnasiebetyg utan komplettering|
|BII||Gymnasiebetyg med komplettering|
|BF||Betyg från folkhögskola|
|AP||Tidigare akademiska poäng|
Applied Data Science masterprogram
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.
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Examen & Intyg
Göteborgs universitet möter samhällets utmaningar med mångsidig kunskap. 37 000 studenter och 6 000 medarbetare gör universitetet till en stor och inspirerande arbetsplats, flödande av kunskap och idéer. Öppenheten är ett signum som genomsyrar verksamheten. Universitetet tar plats i debatten...