Master’s Programme in AI and Machine Learning, 120 HP
Start of studies
Form of education
Campus, Day-time, Full-time
Language
English
Do you want to understand and influence how AI is changing the world? Technologies such as machine learning underpin the intelligent systems used by global tech leaders like OpenAI, Google, and Meta – for example, behind language models like ChatGPT.
This Master's programme will provide you with cutting-edge expertise in artificial intelligence and machine learning – rapidly growing fields that are being applied across an increasing number of industries. You will gain both theoretical depth and practical experience, with the programme closely aligned with the latest research and industry needs.
What will you study?
The programme is designed to meet rapid technological developments and the growing demand for engineers with advanced AI competence. You will acquire knowledge in:
- machine learning and AI algorithms
- Bayesian statistics
- security in AI systems
- digital ethics and entrepreneurship
- research methodology and project work
The education combines theory with practice. You will take part in projects where you apply your knowledge to real-world applications – often in collaboration with companies, public agencies, or other academic departments at BTH.
There are also elective courses, allowing you to deepen your expertise in areas that interest you most. During the final term, you will carry out a Master's thesis, preferably in partnership with an external organisation.
After graduation – what are your career opportunities?
With a Master’s degree in AI and machine learning, many career paths become available. You may work as a:
- machine learning engineer
- AI specialist
- data analyst
- strategic project manager
- technical advisor or developer
Potential employers are growing in number and span across a wide range of industries, such as technology, security, healthcare, transport, and the public sector. Examples of major companies where this expertise is in demand include Sony, Ericsson, Telenor, Volvo, the Police, and the Armed Forces – and the list continues to grow as the technology finds ever-wider applications.
Please contact the Admissions Office with any questions regarding the entry requirements.
The tuition fee is SEK 70,000 per semester. One semester corresponds to 30 ECTS credits. EU/EEA citizens are not required to pay fees.
BTH offers a scholarship programme for both prospective students and current students. If you are a female citizen of one of ten eligible countries and you apply for this program as your first choice, you can also apply for the Swedish Institute Scholarship Pioneering Women in STEM for prospective students. Learn more about scholarships.
Do you have any questions about the programme? Please send them to us using the form on the International Student Guide.
About the programme
The Master’s Programme in AI and Machine Learning is a two-year programme that provides you with in-depth knowledge in data science and intelligent systems. You will learn about the technologies and methods behind today’s – and tomorrow’s – smart systems, including:
- artificial intelligence (AI)
- machine learning (ML)
- neural networks
- ethical issues related to AI
The programme combines theory with practice, giving you both a strong academic foundation and the ability to develop technical solutions that meet the challenges of the future.
Year 1 – Core courses and elective specialisations
The first year begins with two foundation courses: one in applied AI and one in machine learning. These provide a solid base to build upon.
Throughout the year, you can also choose from a range of advanced elective courses, such as:
- advanced machine learning
- deep learning
- security in AI systems
- digital ethics
- intelligent data analysis
- AI and engineering methods
Year 2 – Projects, specialisation and application
The second year begins with a course in research methodology and a project course in software development, where you will apply your knowledge in practice – either in teams or in collaboration with external partners.
You also have the opportunity to take additional elective courses in areas such as:
- robotics
- time series analysis
- predictive methods
Master’s Thesis – Specialisation and real-world application
The programme concludes with an independent Master’s thesis project. Here you will:
- apply your knowledge to a real-world problem
- conduct a study based on current research
- work closely with researchers and industry experts
This is also your opportunity to specialise in an area of your own choosing.
Career Opportunities
After graduation, you will be well prepared for a variety of technical and analytical roles, such as:
- AI developer
- machine learning engineer
- data analyst
- technical consultant or systems developer
You will also have a strong foundation to pursue doctoral studies in AI, machine learning, or related areas. The programme is well-suited for both a career in industry and for those aiming to enter academic research.
Note! The course list is tentative. See the programme syllabus for an established course list.
* Elective course
Autumn semester 2026
Decision Support Systems, 6 HP
Applied artificiell intelligens, 6 HP
Spring semester 2027
ICT Startups and High-Tech Entrepreneurship, 6 HP
Advanced Machine Learning, 6 HP
Autumn semester 2027
Advanced software engineering project in teams, 18 HP
Research Methodology in Computer Science, 6 HP
Security, Privacy, and Compliance in Software Systems, 6 HP *
Multiprocessor Programming, 6 HP *
Technology venture 2: Commercialization of Innovations, 6 HP *
Generative Artificial Intelligence, 6 HP *
Spring semester 2028
Students who apply for a course or programme, and meet the general and specific entry requirements, compete with one another for available places. When there are more qualified applicants than there are places for an education, the places are distributed through a selection. Read about the selection methods and procedure here.
Evaluations and advisory board
The study programmes at BTH are continuously monitored and developed through yearly follow-up dialogues, course evaluations after each completed course, and programme evaluations. Results from follow-ups and evaluations can lead to changes in the programmes. These changes are always communicated to the students.
Each educational programme is tied to an advisory board that discusses issues such as the quality of the programme, its development, and relevance for the labour market. In the advisory board, or a committee to the advisory board, teachers, external members, students and alumni are represented.
Frequently asked questions
Bachelor of Science in Engineering or Bachelor of Science in a technical area. At least 20 credits should consist of courses in Computer Science, Software Engineering or equivalent and include courses in object-oriented programming, 5 credits, algorithms and data structures, 5 credits, database technique, 5 credits and a project course, 5 credits. At least 24 credits should consist of courses in Mathematics and include courses in univariate analysis, 5 credits, linear algebra,5 credits, statistics, 5 credits and discrete mathematics, 5 credits. English 6.
