Software Engineering for AI (master)

## About the programme AI is one of the most transformative technologies of our time - but building safe, robust, and ethical AI software systems requires more than algorithms. Specifically, a systematic and structured approach to software development is needed. However, AI/ML systems differ from traditional software: they are shaped both by code and data, and their behaviour can evolve over time. This creates new demands for quality assurance, versioning, testing, and operations - and requires new ways of combining data science, AI, and software engineering. This master’s programme is built around that combination. Offered in close collaboration with the Jönköping AI Lab and leading industrial partners, it ensures strong ties to both cutting-edge research and industry practice. ### Year one – Foundations in AI and software engineering In the first year, you follow two parallel tracks: - **Core AI and data science:** courses in data science, machine learning, and deep learning give you theoretical and practical insight into algorithms, modelling, and the use of large datasets. - **Software engineering for AI systems:** courses such as Developing AI-enabled systems, AI systems in production, and Research methods in SE4AI provide you with the principles, tools, and methods for engineering AI/ML systems across the full lifecycle. You also strengthen your skills in Python programming and mathematics for intelligent systems, creating a solid base for advanced AI development. ### Year two - Integration and specialisation In the second year, the two tracks converge into an advanced focus on software engineering for AI. You take courses such as Advanced Software Engineering for AI, Developing LLM-enabled systems, and State-of-the-art in SE4AI. You also choose an elective: either a project course where you build and evaluate AI-enabled software in practice, or an industrial placement where you apply your skills in a professional environment. The final semester is dedicated to a 30-credit master’s thesis in software engineering for AI, often carried out in collaboration with industry or research groups. ### What you will learn Throughout the programme, you will develop the ability to: - engineer and deploy scalable AI/ML systems in production, - design, implement, and manage continuous training pipelines for data, code, and models, - understand and implement machine learning, deep learning, Large Language Models (LLMs), and agent-based systems, - apply state-of-the-art research in software engineering for AI, - reflect critically on responsible AI, including fairness, transparency, and ethics. ### Career opportunities Graduates of *Software Engineering for AI* are prepared for specialist roles in one of the fastest-growing fields worldwide. Typical positions include AI Engineer, Machine Learning Engineer, Software Architect for AI systems, Data Scientist, MLOps Engineer, or AI Solutions Architect. Many graduates also move into strategic roles such as Technical Product Manager with an AI focus, or Chief AI Officer. For those aiming for research, the programme also provides a strong foundation for PhD studies in computer science and AI, enabling you to contribute to the development of the next generation of AI solutions.