Advanced Software Engineering for AI 7.5 credits

Course Contents

This course builds on the two previous courses Developing AI-Enabled Systems and AI Systems in Production. It explores advanced concepts in software engineering for AI/ML systems, focusing on quality, security, robustness, and reliability in production. It dives deeper into requirements engineering, QA processes, and advanced testing techniques for AI-enabled systems. Students will learn to implement continuous training, manage model lifecycles using MLOps frameworks, and address failure cases through robust debugging and analysis. Additionally, the course emphasizes interdisciplinary collaboration, data governance and regulations to ensure the development of responsible AI/ML-enabled systems. The course includes the following elements: - Advanced Requirements Engineering (RE) for AI/ML-Enabled Systems - Advanced QA and System-Level Testing for AI/ML-Enabled Systems - Continuous Training, Model Lifecycle Management, and Data Engineering - MLOps: ModelOps, DataOps, and DevOps for AI  - Responsible AI and Ethical Governance  - Debugging and Failure Case Analysis

Prerequisites

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.

Level of Education: Master

Coursecode/Ladok code: T2AMFA

The course is conducted at: School of Engineering

Label Value
Type of course Programme instance course
Study type Normal teaching
Semester Autumn 2027
Study period week 35 - week 42
Rate of study 50%
Language English
Location Jönköping
Time Day-time
Tuition fees do NOT apply for EU/EEA citizens or exchange students 21375 SEK
Syllabus (PDF)
Application code HJ-T1035