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This programme teaches methods for analysis, processing and transmission of large-scale data and signals, using tools from machine learning, signal processing, and information and communication theory. Choose among three specialisations: Images and Vision, Data Science, and Connectivity. Project work is offered in collaboration with tech companies.

Data Science and Information Engineering, Master's Programme

Autumn 2025 / Full-time / Linköping

Closed for late application

Data Science and Information Engineering, Master's Programme - Second admission round mainly for Swedish and EU/EEA students

Autumn 2025 / Full-time / Linköping

We are living in an increasingly networked society. The emergence of new applications such as augmented, virtual and extended reality, and the Internet of Things, are set to revolutionise the coming decades. The exponential growth in the capability of artificial intelligence and machine learning, and the proliferation of wireless communication devices, require skilled engineers to drive technological development and inspire new inventions. This programme provides tools to develop these new technologies. It is highly competitive – you must possess advanced skills in mathematics, programming, and a dedication to your education.

Complex networks and signal analysis

Mandatory courses include machine learning, complex networks and big data, multidimensional signal analysis, information and communications engineering, as well as distributed information processing and learning.

From the second semester you follow one of these specialisations:

  • Images and Vision: Courses mainly on image processing and computer vision.
  • Data Science: Advanced information processing and machine-learning knowledge for the analysis of and inference from big data.
  • Connectivity: Wireless systems and their fundamentals, with a range of courses on communications and information storage, compression, and transmission.

Compulsory project course and lab sessions

Teaching consists of lecture-based instruction and tutorials. Most courses include computer project lab sessions. The third semester has a compulsory project course during which you learn about project management, apply your knowledge to solve a larger problem, and work in teams with other students. The final semester is devoted to your thesis, which may be carried out either in collaboration with a tech company or as an internal project with the University. Ericsson, Saab, Sectra, and Qualcomm are among the major tech companies with a presence in Linköping.

Excellent research opportunities

Linköping University has world-class research in computer vision, data science, and the development of 6G – the next-generation cellular network technology. As a student, you will be fully immersed in this environment. We can help put you in touch with groups and companies in these fields.

Work as an engineer or continue with research

The programme prepares you for a career as engineer in industry. If you are interested in research, you will also be qualified for postgraduate studies towards a PhD degree.

Syllabus and course details

Here is a preliminary schedule for all four semesters (two years). Detailed information related to the first semester can be found in our Study Information database (big blue button below). For entry requirements and tuition fees, please click the ”Admission requirements” tab at the top of the page.

Semester 1 (compulsory courses)

, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits

Semester 2 (compulsory and elective courses)

, 6 credits
, 6 credits
, 6 credits
Digital and wireless communications, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits

Semester 3 (compulsory and elective courses)

, 12 credits
, 6 credits
, 6 credits
, 12 credits
, 6 credits
, 6 credits
, 6 credits
, 6 credits
Distributed information processing and machine learning, 6 credits

Semester 4

, 30 credits

Research

Application and admission

Application document checklist

  1. Diploma(s) of your degree(s) from an internationally recognized university, or a .
  2. Transcripts of completed courses and grades for each semester included in your degree. If you have had courses credited/transferred from previous studies, you must also submit official transcripts for those courses.
  3. Proof that you meet the specific entry requirements, for example relevant pages of course syllabuses (course descriptions), if the required courses/subjects are not clearly stated on your transcript.
  4. Proof of English language proficiency.
  5. A copy of your passport.

Much of what you need to submit – and how – is based on where you completed your studies. Find out how to do things right on University Admission: .

University Admissions: .

Letters of intent or recommendation are not required.



Essential information

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