Program Overview

Degree Programme in Engineering Mathematics

The Degree Programme in Engineering Mathematics is designed to provide students with a comprehensive education in engineering mathematics. The programme syllabus for studies starting in Autumn 2026 outlines the structure and content of the programme.

Programme Objectives

The programme objectives are not explicitly stated in the provided context. However, the programme syllabus outlines the extent and content of the programme, which includes mandatory courses, conditionally elective courses, and optional courses.

Extent and Content of the Programme

The programme consists of five study years, with a range of courses offered in each year. The courses are designed to provide students with a strong foundation in engineering mathematics, as well as specialized knowledge in areas such as automatic control, optimization, and computer science.

Mandatory Courses

The following mandatory courses are part of the programme:

• SA1006 Engineering Skills in Engineering Mathematics (8.5 credits)
• EL1000 Automatic Control, General Course (6.0 credits)
• SF1811 Optimization (6.0 credits)

Conditionally Elective Courses

The following conditionally elective courses are part of the programme:

• SA120X Degree project in Engineering Mathematics, first cycle (15.0 credits)
• EF112X Degree Project in Electrical Engineering, First Cycle (15.0 credits)

Optional Courses

A range of optional courses are available, including:

• DD1351 Logic for Computer Scientists (7.5 credits)
• DD1367 Software Engineering in Project Form (9.0 credits)
• DD1368 Database Technology (6.0 credits)
• DD1420 Foundations of Machine Learning (7.5 credits)
• DD2350 Algorithms, Data Structures and Complexity (9.5 credits)
• DD2352 Algorithms and Complexity (7.5 credits)
• DD2395 Computer Security (6.0 credits)
• DD2421 Machine Learning (7.5 credits)
• DH1623 Human-Computer Interaction, Basic theory (4.5 credits)
• DH1624 Human-Computer Interaction, Basic project (3.0 credits)
• EI1320 Electromagnetic Theory (9.0 credits)
• EL2810 Machine Learning Theory (7.5 credits)
• EP1100 Data Communications and Computer Networks (7.5 credits)
• ID1200 Operating Systems (6.0 credits)
• IS1500 Computer Organization and Components (9.0 credits)
• SE1010 Solid Mechanics, Basic Course with Project (12.0 credits)
• SE1055 Strength of Materials and Solid Mechanics, Basic Course with Energy Methods (9.0 credits)
• SF1677 Foundations of Analysis (7.5 credits)
• SF1678 Groups and Rings (7.5 credits)
• SF1691 Complex Analysis (7.5 credits)
• SF2701 Financial Mathematics, Basic Course (7.5 credits)
• SF2812 Applied Linear Optimization (7.5 credits)
• SF2832 Mathematical Systems Theory (7.5 credits)
• SF2863 Systems Engineering (7.5 credits)
• SF2930 Regression Analysis (7.5 credits)
• SF2940 Probability Theory (7.5 credits)
• SF2955 Computer Intensive Methods in Mathematical Statistics (7.5 credits)
• SG1218 Fluid Mechanics (4.0 credits)
• SG1220 Fluid Mechanics for Engineers (6.0 credits)
• SI1155 Theoretical Physics (6.0 credits)
• SI1162 Statistical Physics (7.5 credits)

Implementation of the Education

The implementation of the education is not explicitly stated in the provided context. However, the programme syllabus outlines the structure and content of the programme, which includes a range of courses and study periods.

Eligibility and Selection

The eligibility and selection criteria for the programme are not explicitly stated in the provided context. However, the programme syllabus outlines the extent and content of the programme, which includes information on the courses and study periods.

Appendix 1: Course List

The course list is included in the programme syllabus and outlines the mandatory, conditionally elective, and optional courses available in the programme.

Appendix 2: Specialisations

The specialisations available in the programme are not explicitly stated in the provided context. However, the programme syllabus outlines the extent and content of the programme, which includes information on the courses and study periods.