Artificial intelligence and data analysis

The possibilities of artificial intelligence and data analysis at your fingertips. As of spring 2017, Jamk University of Applied Sciences Institute of Information Technology has put a strong emphasis on development and application of artificial intelligence and data analytics for various purposes.

Our work

The main weight is on application of products based on open source code either to solve a real life problem of business and industry or solve problems in hackathon events using artificial intelligence or data analytics, or on other interesting cases. Staff members (lecturers and specialists) as well as students (writing a thesis or doing their practical training) work on artificial intelligence and data analytics.

All our work

Deep learning

Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data.

Machine learning

Machine learning is a subset of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience/data without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves.

Companies

If your company needs information on possibilities of applying artificial intelligence or data analytics in your company, or if you have a clearly identifiable need for either of these, please contact us.

Students

We aim to continuously take in new students into our group as trainees or thesis writers. If you got interested, please submit a free-form application.

Contact us!

Mika Rantonen

Yliopettaja, Principal Lecturer
IT-Instituutti, Institute of Information Technology
Teknologia, School of Technology
+358407167269

Related

Master's Degree

Master of Engineering, Artificial Intelligence and Data Analytics

Application period: 8.1.2025 - 22.1.2025

Study mode:

Part-time studies

Education starts: 29.8.2025