The Academies

Robotics Academy and Artificial Intelligence Academy of Satakunta University of Applied Sciences are new ways of studying. Suitability as an Academy student is tested by a personal interview. Instead of the traditional classroom or online education the students learn by working on companies´ real automation, robotics or artificial intelligence-related problems and development projects. Academies are RoboAI´s expert incubators and they prepare the students directly to the needs of the working life.


The success story of year 2018

SAMK introduced the academy model in the autumn of 2017 by launching Robotics Academy where studies lead to a Bachelor´s degree. During the first year, more than 30 projects of varying extents were implemented. The students selected for academy studies conduct their studies by working on real technology projects. Robotics Academy studies are available for Electrical and Automation Engineering and Mechanical Engineering students as well as Business Information Systems students.

The academies function as colliders between companies and students by offering practical students new ways of studying and companies possibilities of implementing technology projects together with students. The model enables finding innovative and fresh perspectives and conveying new technology competence to companies in a form that is as easily exploitable as possible.

The topics for the projects come from companies and communities and there is always a concrete need, i.e. after the projects there should be a functional final outcome that meets the needs of the customer. The result can be e.g. a robot application, production simulation, development of a production cell or a technology data packet/info pack.


Pepper labrassa.

By educating students in a practical manner, based on the needs of the companies, we are building robotics-connected intellectual competence in the region and by Academy´s slow recruiting we ensure the availability of workforce for companies. A major part of the students wish to stay at their place of study also to work, so it is important that they possess competence that serves the companies in the region.

Mirka Leino, Principal Lecturer in Robotics Academy, Head of Automation Research Team

AI Academy

Artificial Intelligence Academy focuses on developing future artificial intelligence competence

Artificial Intelligence Academy is a highly practical method of studying. The students selected for academy studies conduct a part of their studies by working on real programming and artificial intelligence-related technology projects. The topics for the projects come from the companies and communities in the region and they always have some concrete need.

The primary goal is that the students take responsibility for developing their own learning, learn to function in close cooperation with different people and as a part of the companies´ development projects. As the project progresses, budgeting, the stages of project management, methods of communication and company´s modes of operation become familiar. Practical doing and solving real challenges develop the students´ innovativeness when they see the issues closer and can test their own boundaries.

Suitability as an Artificial Intelligence Academy student is tested at a personal interview. Business Information Systems students and Electrical and Automation Engineering students who specialize in Information Technology can apply for Artificial Intelligence Academy. The students selected start their academy studies during their second year of studies. The student selection of academy emphasizes teamwork skills, enthusiasm, practicality and interest in the field to meet the needs of working life as comprehensively as possible. From a pedagogical point of view, academies utilize studification of work, project learning and teaching methods of exploratory learning. A good applicant is interested in and enthusiastic about artificial intelligence, motivated and a sociable team worker.

The studies include e.g. the following modules: Computational Intelligence, Data Analytics and Machine Learning.