About the course

The student shall acquire an understanding of established practices and current research related to software development, as well as the impact and use of data science in software engineering.

Course content

The course contains the following elements:

The course conveys perspectives on software development techniques and joint project work, as well as current advances in software development. Some techniques and methods that are addressed are:

- Data-driven innovation and data-driven decision making in research and development of artifacts
- A-B testing, data collection techniques
- Scrum and Kanban Software development framework that implements Agile and Lean methods
- Distributed software development
- Test-driven development
- DevOps/DataOps/MLOps principles and practice
- Challenges to achieving high-performance groups for software development
- Data-driven innovation and ML workflow lifecycle: how collected user data can be introduced to the software development cycle, during the design, implementation, evaluation and maintenance phases.

Entry requirements and selection

Entry requirements

1. Bachelor of Science (at least 180 higher education credits) in computer science or related subjects such as mathematics, informatics, telecommunications, electrical engineering, physics.
2. Knowledge equivalent to English 6 at Swedish upper secondary level.
3. At least 15 credits in programming.
4. At least 7.5 credits in mathematics.

Selection

100% University credits completed

Course literature

Course evaluation

The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).

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