Computer Science - Applied Data Science Malmö University

Overview

In an era marked by rapid digital transformation, the Master's programme in Computer Science - Applied Data Science at Malmö University stands out as a vital educational pathway. This two-year, full-time course focuses on equipping students with the necessary tools and methodologies to harness the burgeoning potential of digital data across various sectors. The ever-increasing volume of data generated daily necessitates skilled professionals who can extract meaningful insights and drive innovation. This interdisciplinary programme provides a robust foundation in the state-of-the-art methods and algorithms of data science, complemented by practical experience with cutting-edge tools and systems used in the industry.

Malmö University is renowned for its quality education and strong connections to the tech industry. The university's industry advisory council ensures that the curriculum aligns with the skills employers seek in graduates. Students benefit from a diverse, international learning environment that fosters innovation and entrepreneurship. Malmö is a vibrant city, recognized as a hub for start-ups, with eight new companies founded daily, making it an ideal setting for aspiring data scientists.

The tuition fees for the Master's programme in Computer Science - Applied Data Science are as follows:

• International Fee: SEK 300,000 per full programme
• European Fee: SEK 0 per full programme

Visit the Fees and Funding section for a breakdown in your local currency.

The curriculum is structured to provide a comprehensive understanding of data science through a series of modules:

• Artificial Intelligence for Data Science (15 credits)
• Statistical Methods for Data Science (7.5 credits)
• Data and Society (7.5 credits)
• Exploratory Data Analysis, Visualisation and Storytelling (7.5 credits)
• Data-Driven Methodologies for Software Development (7.5 credits)
• Advanced Machine Learning (15 credits)
• Research Methods of Computer Science and Fundamental Computational Theory (7.5 credits)
• Big Data Analytics on Cloud Computing Infrastructures (15 credits)
• Capstone Project in Applied Data Science (7.5 credits)
• Master’s Thesis in Applied Data Science (30 credits)

Graduates from this programme will possess strong competencies in managing, modelling, and visualising big data, making them well-prepared for various roles in the data science field. They can expect to find opportunities in sectors such as technology, logistics, financial services, healthcare, and digital marketing. The skills acquired during the programme also lay a solid foundation for those interested in pursuing doctoral studies in data science or related fields.