Programme Outlines and Overviews

Research Methods in SE4AI 7.5 credits

Course content

This course introduces research methodologies and practices in the context of software engineering, with a focus on AI/ML-enabled systems. Students will learn to design, conduct, and evaluate empirical studies while exploring qualitative, quantitative, and mixed-method approaches. The course also covers techniques for systematic literature review, data analysis, and academic writing. By the end of the course, students will be equipped to critically analyze research in SE and contribute to the field through their own research projects. The course includes the following elements: - Introduction to Research Methods in Software Engineering - Formulating Research Questions and Hypotheses - Empirical Research Techniques - Data Collection and Analysis - Research Validity and Reliability in SE Research - Writing and Presenting Research in SE

Entry requirements

Passed courses at least 90 credits within the major subject computer engineering, computer science, informatics, information systems or information technology, including a minimum of 15 credits in mathematics and at least 30 credits in programming/software development, or alternatively passed courses at least 150 credits from the programme Computer Science and Engineering, and taken AI Systems in Production, 7.5 credits and Machine Learning , 7.5 credits.

Level: Second cycle

Course/Ladok-code: T2FIOT

School: School of Engineering