MSc Data-driven Health
The master's programme in Data-driven Health equips you with the skills to employ data to transform healthcare and improve people's health and health systems. You will acquire technical skills in data processing, data mining and machine learning, combined with expertise in health systems and systems biology. After graduation, you face exciting career opportunities in a quickly expanding field. This is a new programme expected to open for application in October 2024.
Data-driven Health at KTH
The master's programme in data-driven health provides expert knowledge on how data can be used to change and streamline healthcare and improve people's health. The focus is on using health data from healthcare, self-produced data, community data and health data from other sources in the analysis. You will explore different ways of processing, storing, modelling and analysing data to put data-driven insights into a complex context. You will gain an understanding of the type of data that exists, how it is structured, and how to adapt it for effective analysis. "Data curation" and "data governance" are also technical parts of the programme.
During your studies, you will work with real cases, for example, by analysing data on different diseases and looking at young people's mental health. You will also gain valuable insights into healthcare organisations to prepare you for your future career.
The master's programme offers plenty of opportunities to specialise through project courses and elective courses. Elective courses focus on imaging, distributed learning and advanced topics. Project courses allow you to work with faculty and clinicians on applied projects covering sports, physiology and health systems. During the first year, you take mandatory courses in Statistics, Machine Learning, Databases and Warehouses, Ethics and Socio-Cultural Perspectives on Technology. The second year is dedicated to project courses, advanced topics in different directions and the master's degree project.
The programme emphasises complementary skills such as problem-solving, teamwork, and project management, aligned with CDIO principles. You will have access to in-house cloud infrastructure, makerspaces and datasets, and most courses offer project assignments to complement traditional lectures. The programme is heavily focused on applying advanced data tools in actual practice.
The programme complements technical skills with insights into legal, ethical and socio-cultural aspects of health data. The research at KTH complements the programme and cover all aspects of data-driven health, from semantic engineering to FAIR data management, to applied data analysis and data engineering, machine learning and artificial intelligence. The curriculum provides a highly interdisciplinary approach that enables students to acquire a unique and individualised expertise that appeals to many employers.
This is a two year programme (120 ECTS credits) given in English. Graduates are awarded the degree of Master of Science. The programme is given mainly at the KTH Flemingsberg campus in Stockholm by the School of Engineering Sciences in Chemistry, Biotechnology and Health (at KTH).
Future and career
The combination of technology and data with an emphasis on health, taught in the programme, provides an attractive profile for a professional career in the medical technology, pharmaceutical industry, medical services and even in the public sector (government, non-profit). This area is expanding rapidly worldwide, providing graduates with career opportunities in various fields, such as engineering, analysis, data science, research, journalism and consultants. A degree from the programme will also open doors to an academic career and further doctoral studies.
Sustainable development
Graduates from KTH have the knowledge and tools for moving society in a more sustainable direction, as sustainable development is an integral part of all programmes. The three key sustainable development goals addressed by the master's programme in Best Practice are:
In the programme, you will study, learn, and apply health data to strengthen people’s health and healthcare systems and provide equitable access to health for all. Courses on legal and ethical aspects, socio-cultural perspectives, and privacy and security temper the technological aspects. The acquired knowledge is applied to the innovative design of data systems that enable access to health data, improve health literacy, and improve the design of data systems and models that can cure diseases and improve health.
Research and faculty
The programme is provided mainly at the KTH Flemingsberg campus with courses provided by KTH's Department of Biomedical Engineering and Health Systems . The department spans a vast field, from cellular and molecular levels to complex systems and the broader subject fields of health, environment, and materials. Research is conducted in Biomedical Imaging, Health Informatics and Logistics, Neuronic Engineering and Ergonomics. The department's teaching staff have extensive experience working with a student-centred and student-active pedagogy, where intractable problems are the focus. The department also has a software makerspace with a cloud solution for executing machine learning. Thisis valuable for the students in the programme who conduct projects that require extensive and expensive hardware. The programme has close links and collaborations with large parts of the healthcare system in Stockholm and Sweden, as well as with government and industry.
The programme is provided mainly at the KTH Flemingsberg campus with courses provided by KTH's . The department spans a vast field, from cellular and molecular level to complex systems and over the broader subject fields of health, environment and materials. Research is conducted in areas such as Biomedical Imaging, Health Informatics and Logistics, Neuronic Engineering and Ergonomics. The teaching staff at the department have extensive experience in working with a student-centered and student-active pedagogy, where intractable problems are the focus. The department also has a software makerspace that contains a cloud solution for executing machine learning. This is valuable for the students in the programme who conduct projects that require large and expensive hardware.
Faculty involved in the programm
