Master's Programme (120 credits) in Information Technology
As an information technologist, you can help solve many of society’s future challenges in, for example, autonomous vehicles and health care. This master’s programme develops your knowledge of information technology with a special focus on machine learning and computer technology.
About the education
Innovative environments, methods and tools
The education at Halmstad University is characterised by our profiling as a university that drives innovation. This program is strongly linked to the University's research in AI and machine learning. The focus is on the development of digital services based on knowledge extracted from data.
Part of the programme is carried out together with master’s students in informatics. This gives you an interdisciplinary perspective and the opportunity to develop technical solutions that match existing needs in society.
Courses and competencies in focus
In the Master’s programme in Information Technology, you develop theoretical and practical skills for research, development and implementation of computer technology. The basis of the programme is a computer technology perspective on information technology in close collaboration with industry.
You obtain in-depth knowledge of computer science for the subject areas machine learning, image analysis, parallel computer programming, data mining and digital service innovation. At the same time, you gain experience of project work linked to research and service development, all in an international environment.
The programme is conducted in English.
The programme is carried out in collaboration with industry and the public sector.
Bachelor of Science degree (equivalent of 180 Swedish credit points/ECTS credits at an accredited university) in an engineering subject or in computer science. Courses in computer science, computer engineering or electrical engineering of at least 90 higher education credits, including thesis. Courses in mathematics of at least 30 higher education credits or including calculus, linear algebra and transform methods. Applicants must have written and verbal command of the English language equivalent to English course 6 in Swedish Upper-Secondary School.
The courses listed below are included in the programme starting autumn 2021 (may be subject to change).
* included in the programme main area Computer Science and Engineering.
- Artificial Intelligence, 7.5 credits *
- Perspectives on Data Science, 7.5 credits *
- Algorithms, Data Structures and Problem Solving, 7.5 credits *
- Engineering Mathematics, 7.5 credits
- Edge Computing and Internet of Things, 7.5 credits *
- Image Analysis, 7.5 credits *
- Learning Systems, 7.5 credits *
- Big Data Parallel Programming, 7.5 credits *
- Data Mining, 7.5 credits *
- Digital Service Innovation, 7.5 credits *
- Deep Learning, 7.5 credits *
- Thesis, 30 credits *
- Thesis, 30 credits *
- Computer Vision in 3D, 7.5 credits *
- Artificial Intelligence for Health, 7.5 credits *
- Intelligent Vehicles, 7.5 credits *
After the education
The programme leads to a Degree of Master of Science (120 credits) with a major in Computer Science and Engineering.
Opportunities for further studies
After the programme, you are qualified to apply for doctoral or PhD studies, for example in the University's third cycle courses in information technology.
The Master's programme in Information Technology prepares you for an advanced development role within the industry.
Bachelor of Science degree (equivalent of 180 Swedish credit points / ECTS credits at an accredited university) in an engineering subject or in computer science. Courses in computer science, computer engineering or electrical engineering of at least 90 higher education credits, including thesis. Courses in mathematics of at least 30 higher education credits or including calculus, linear algebra and transform methods. Applicants must have written and verbal command of the English language equivalent to English course 6 in Swedish Upper-Secondary School.
Selection is made on the basis of the required educational background.
Language of instruction:
Teaching is in English.
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