Master’s programme in Artificial Intelligence
The Master of Artificial Intelligence (AI) is a two-year advanced programme organized by the Department of Knowledge Engineering. The focus of this programme is on the understanding, design and creation of intelligent systems in both software (e.g., computer games) and hardware (e.g., robotics). The term “Artificial Intelligence” dates back to 1956 when John McCarthy defined it as “the science and engineering of making intelligent machines”. Even though nowadays we are still far from building machines that can pass the famous Turing test (A. Turing, Mind, 59 (236), 1950 - a test to determine whether a machine shows human intelligence), Artificial Intelligence has become a very active domain in both academia and industry. It has achieved to build computer programmes and robots that learn from experience, recognize patterns in vast amounts of data, and reason strategically in complex decision-making situations. Artificial Intelligence is, therefore, an interdisciplinary field where domains such as Computer Science, Mathematics, Psychology, Biology, Philosophy and Economics meet.
The impact of the field of Artificial Intelligence is pertinent due to the key role it plays for technological applications that have become indispensable in society, including data mining (e.g., detection of fraudulent credit card transactions), automated trading software in real markets, intelligent network routing on the internet, robotic space exploration, sensor networks for medical applications and many more. In this master programme, you are trained to become an expert in Artificial Intelligence, capable of dealing with today's and future challenges.
The Master of Science in Artificial Intelligence provides you with a thorough knowledge of algorithms, methods and techniques from the domain of Artificial Intelligence. It enables you to understand and develop intelligent systems in a wide variety of settings. You will be able to develop computational solutions to problems and provide up-to-date scientific and technological advice in a professional setting. The Artificial Intelligence programme is based on the Project-Centred Learning (PCL) education system. The PCL education system incorporates a number of important skills, including working in teams, interview techniques, project planning and presentation. Each of these skills will be important to future employers. During the program, e you will acquire a scientific, problem-solving attitude and will be able to find the relevant literature and software. In addition, you are able to critically evaluate scientific papers and software solutions. Taken together, after obtaining the Master of Science degree in Artificial Intelligence you will possess all the basic competencies of a scientific researcher, have excellent writing and presentation skills, and are trained to work in a team.
The Master degree in Artificial Intelligence provides good perspectives in obtaining a position at a research institute or research-oriented company. This includes doctoral and management positions at universities, governmental institutions, and R&D departments in the industry. Others will find their way to management and consultancy positions involving advanced knowledge processing or will start their own company.
The master’s programme in Artificial Intelligence is a two-year programme taught entirely in English and leads to the title Master of Science (M.Sc.).
In the first year, you follow courses on topics concerning machine learning, multi-agent systems, intelligent search, games and knowledge discovery. The courses on these topics are complemented with two projects that enable you to combine and apply what you have learned in these courses.
During the first semester of the second year, the programme allows you to pursue personal interests. You can partake in an international exchange, an elective semester, participate in a company or a research internship. In the second semester of the second year, you will work on your master’s thesis on a research topic of your personal interest, under the supervision of one of the academic staff members. You can do this master’s thesis research internally or externally at a company or in collaboration with one of the partner universities of DKE.
The master’s programme in Artificial Intelligence covers a wide range of subjects emphasising the following eight research topics:
- machine learning to explore relations in datasets
- multi-agent systems of collaborating autonomous intelligent systems
- situated agents that can operate in environments using uncertain observations
- formal techniques for reasoning in agents
- techniques for representing knowledge
- intelligent techniques for playing and solving board games and controlling virtual characters in commercial video games
- extracting interesting and non-trivial information and knowledge from unstructured text
- relational learning to extend machine learning techniques to deal with expressive logical or relational representations.
In addition, master’s thesis research can be carried out that relates to projects offered by institutes and companies in the region. The members of the scientific staff are all actively involved in the department's ongoing research programme. As a result, the educational content of the courses in the master’s programme in AI relates directly to the research performed.
Schedule of the programme
- Block 1: Autonomous Systems
- Foundations of Agents
- Multi-agent Systems
- Intelligent Search & Games
- Research project
- Data Mining
- Ontology Engineering and Semantic Web
- Relational Learning
- Text Mining
- Research project
- Optional programme: (international) exchange/internship/research at the department/additional optional courses
- Master’s thesis
Admission requirements and Application procedure
If you wish to apply for the master’s programmes in Artificial Intelligence or Operations Research, you may apply directly via the My UM portal on the University website (no Studielink registration necessary!).
Please prepare all required documents (i.e., diploma, grade list, a copy of your passport, etc.) before filling out the online application form.
There are two moments throughout the year when students can begin the programme: at the start of the fall semester in September and at the start of the spring semester in February. Please be aware that the processing and approval of an application by the Board of Admissions takes time. Your application has to be fully completed and approved by the Board of Admission before the 1st of September for the fall semester and before the 1st of February for the spring semester. Therefore, we encourage you to submit your application as soon as possible and we require that you complete your online registration no later than the following deadlines:
- 1st of August for the fall semester;
- 6th of January for the spring semester.
If you missed the “online registration” deadline contact our admission office. Please note that if you have not yet obtained the diploma which confirms your eligibility, you can still apply by submitting a certified transcript. Your admission will then be under the condition that you obtain and submit a copy of the above-mentioned diploma.
Non-EU residents should be aware that applying for a visa and the evaluation of your diploma may take longer than two months. Therefore, apply as early as possible.
Once you have applied for one of our master’s programmes online and you have been accepted by the Board of Admission of the Department of Knowledge Engineering you will receive an invoice. To complete the application process and formalize your registration as a student you need to send back your signed invoice for payment of tuition fees to the Registration Office.
Please note that to be eligible to participate in the educational programme, each student is required to finish the registration process completely. Therefore, make sure you complete the payment details as the final step of your registration before the above-mentioned deadlines.
Master’s Open Days:
- Saturday 13 October 2012
- Saturday 02 March 2013
"Having received a Top Talent Scholarship from TUDelft and a High Potential Scholarship from UM, I had to decide which master programme and university to choose.
As much as I have enjoyed Computer Science as my background, I cannot forget how excited I got, seeing the course titles of the Artificial Intelligence master programme offered by DKE. Moreover, the reputation of the faculty for its Project-Centred Learning convinced me that this study would provide me with both the theoretic and the pragmatic skills needed for my future career.
I benefited from the dynamic classes, state-of-the-art course material, the cosy atmosphere at DKE, and finding the opportunity to accomplish my internship and thesis project at Philips Research where I have also started my career, after the offer I received from them. I am so content with the choice I made ."
Aisan Maghsoudi, Alumna
“When I reached the end of my bachelor, I wanted to extend my knowledge about the subjects seen in the courses. Thus, I decided to continue with a Master’s study. Maastricht was a great choice for it because it had both an innovative and dynamic way of teaching while keeping a great quality. The Project-Centred Learning (PCL) approach made me responsible for my learning by setting milestones while leaving space for my creativity. This gave me the taste for research and is one of the reasons why I am now doing a PhD. The Department of Knowledge Engineering has a great international reputation while being human-sized. This allows for easy contacts with the teaching staff and other students as well as having great career prospects and opportunities.
Today I am not regretting my choice; the knowledge acquired over the years has given me the ability to build a strong basis for my career. The PCL has given me the skill to find the tools I need to perform a task but also to set up short and long-term goals to successfully achieve a task. Not only is it a key for a successful research project like a PhD, but also in the everyday life.”
Philippe Uyttendaele, PhD student
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Last updated September 20, 2018