The course is part of the programme Computer Science: Applied Data Science, master’s programme, and can be included in the master's degree in computer science (120 credits).
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.
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.
Knowledge and understanding
For a passing grade the student shall be able to:
- Demonstrate an understanding of cultural and social challenges in assembling, leading and participating in high-performance groups for software development
- Describe the characteristics of different software development techniques
Competence and abilities
For a passing grade the student shall be able to:
- Identify how activities can be reviewed and improved using collected user data
- Prepare and choose strategies and methods for implementing effective software development projects, as well as deploying and maintaining ML systems in production reliably and efficiently
- Practice the use of academic language to present and reflect, in written as well as verbal form
Evaluation abilities and approach
For a passing grade the student shall be able to:
- Make assessments in the field of computer science, taking into consideration relevant practical, scientific, societal and ethical aspects
- Identify his or her need for further knowledge and take responsibility for his or her own continued development in the field
Requirements for pass: the course is assessed through
- a pre-study report in a group presented verbally and in writing (3.5 credits, UA), and
- an individual written reflection (4 credits, UA).
An A-E passing grade requires that all parts have been completed and passed. The final grade is based on the individual written reflection.
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).
When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.
The syllabus is a translation of a Swedish source text.