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Master's Programme (120 credits) in Information Technology, 120 credits

At this programme you can further develop your knowledge and ability in Information Technology with a particular focus on machine learning and data science. You also gain experience in project work for research and service development, and of acting in an international environment. Typical topics for the courses of the programme are artificial intelligence, big data parallel programming, data mining and digital service innovation. These topics are all relevant for many future societal challenges such as applications in autonomous vehicles and health care.

The main goal of this programme is to develop both theoretical and practical competence for research, development and implementation in Computer Science and Engineering. The basis of the programme is a data science oriented perspective on information technology with close collaboration with the industry. A part of the programme is studied in connection to the Master’s programme in Informatics, where students from both programmes get experience of cross-disciplinary collaboration to develop technical solutions and identify both societal needs and new potential services.

In the first semester basic courses within the main area of the programme are taken. These courses are mainly of introductory and overview character of relevant methods and theories within the data science area, but also containing societal and ethical aspects. In the second semester the student takes courses for deeper knowledge in machine learning and image analysis, but also shall gain understanding of the possibilities and limitations of distributed computations and programming of parallel platforms. These courses build on the courses taken in the first semester. In the third semester there are courses where students can develop a higher level perspective on extracting knowledge from data and to use this knowledge for developing new digital services. During this semester the master thesis work is also started. In the fourth semester the thesis work is done and an elective course is chosen in a specialization area that can be related to the thesis work.

Instruction is generally in the form of lectures, seminars, laboratory work, consultation and project work. Several courses have compulsory assignments that shall be presented both in writing and orally.

The programme is offered in English.

The degree is 120 credits. For obtaining the degree is required that the prerequisites of the programme are fulfilled and in addition to this that at least 120 credits have been obtained following the directions in the Study Programme.

Upon completion of the degree programme, a degree certificate will be issued bearing the degree programme title in Swedish: Teknologie masterexamen med huvudområdet datateknik. In English: Degree of Master of Science (Two Years) with a major in Computer Science and Engineering.

Specific eligibility requirements
Bachelor of Science degree (or equivalent) 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.

Degrees from other countries than Sweden must be at the same level as a Swedish Bachelor's degree in electrical engineering.

Applicants must have written and verbal command of the English language equivalent to English course 6 (Swedish Upper-Secondary School). This can be proved by grades from English education or by such tests as:
  • IELTS: score (Academic) of 6.5 or more (with none of the sections scoring less than 5.5)
  • TOEFL paper based: score of 4.5 in written test and a total score of 575
  • TOEFL internet-based: score of 20 in written test and a total score of 90

Selection rules and procedure
Selection is made on the basis of the required educational background.

The programme is intended for full time studies over four semesters.

Instruction is generally in the form of lectures, seminars, laboratory work, consultation and project work. Several courses have compulsory assignments that shall be presented both in writing and orally. Instruction in all courses will be conducted in English.

A student who takes part of the education at another university, for example as part of an exchange programme, may include other, equivalent courses from the other university for the degree.

The following courses are offered within the programme
(1st  First level, 2nd  Second level)
Courses marked with asterisk (*) are included in the pro
gramme main area.

Semester 1

Articial Intelligence, 7.5 credits (2nd)*
Perspectives on data science, 7.5 credits (2nd)*
Algorithms, Data Structures and Problem Solving, 7.5 credits
Engineering Mathematics, 7.5 credits (2nd)

Semester 2
Edge Computing and Internet of Things, 7.5 credits (2nd)*
Image Analysis, 7.5 credits (2nd)*
Learning Systems, 7.5 credits (2nd)*
Big Data Parallel Programming, 7.5 credits (2nd)*

Semester 3
Data Mining, 7.5 credits (2nd)*
Digital Service Innovation, 7.5 credits (1st)
Deep Learning, 7.5 credits (2nd)*
Thesis, 30 credits (2nd)*

Semester 4
Thesis, 30 credits (2nd)*

Elective courses:

Computer Vision in 3D, 7.5 credits (2nd)*
Articial Intelligence for Health, 7.5 credits (2nd)*
Intelligent Vehicles, 7.5 credits (2nd)*
The University reserves the right to cancel courses chosen by less than 12 students.

Programme information

Rate of study:
Full time(100%)/daytime

Study period:
Autumn semester 2019

Educational level:


Study programme:
Link to study programme (PDF)Study programme     

Further information:
Programme director
Martin Daniel Cooney

Updated 2018-09-05