Computer Science: Applied Data Science, Master's Program (Two-Year)

Utbildningsfakta

Kod: TACAS

This two-year master’s programme provides you with understanding of the state-of-the-art methods and algorithms of data science through hands-on experience with the latest tools and systems in the industry. The goal is to develop the right tools to extract the full value from the ever-increasing growth of digital data. After graduation, you will be qualified to work in a range of positions in data-centred projects as well as pursue PhD studies in data science. Data Science is an emerging and multidisciplinary field that requires knowledge and skills in subjects such as computer science, mathematics and communication technologies. During this programme, you will get a comprehensive understanding of the fundamental aspects of data modelling, computational techniques and statistical analysis. You will apply these skills to real-world problems and build a portfolio of projects demonstrating solutions to current business and societal challenges. You will have the opportunity to conduct original and innovative research, working with industry partners and academia during the capstone project course and thesis work. The programme is built around an international research environment at Malmö University. The teaching staff includes experts in artificial intelligence, data processing and analysis, software development for big data and cloud architectures, modern software methodologies, and data visualisation.

Behörighet

1. Bachelor's degree or master's degree (at least 180 credits) in computer science or related topics such as mathematics, informatics, telecommunications, electrical engineering, or physics. 2. At least 15 credits in programming. 3. At least 7.5 credits in mathematics at university level. 4. English 6 Or English level 2.

Utbildningstillfällen

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• Computer Science: Applied Data Science, Master's Program (Two-Year)

  Malmö University

  MALMÖ

  Startdatum: 30 augusti 2027

  Slutdatum: 3 juni 2029

  Studietakt: 100 %