Master of Engineering, Intelligent Systems

Industrial automation is undergoing rapid development due to digitalization and technological improvements. As a student of the Masters degree programme in Intelligent Systems you will gain knowledge of how to model and simulate industrial processes, you will be able to identify opportunities for industrial decision-making and learn how to implement intelligent solutions. You will also learn how to apply machine learning methods to solve industrial problems by using classification, regression, detection, and optimization. As a student you will understand the importance of thorough testing and evaluation of models and of high-quality data to succeed with the data-driven decision-making process. You will also develop an understanding of the ethical, sustainability and security challenges of intelligent industrial automation.

Structure of studies

The Master’s degree programme in Intelligent systems (60 ECTS) consists of degree specific professional studies (30 ECTS) and a Master’s thesis (30 ECTS).

The studies are primarily designed for students who are working. Tuition in the Master’s degree programme is organized so that studying can be combined with full-time work during a period of two years. During these two years, the studies are scheduled for two days a month from September to June. The studies consist of virtual parts and intensive course days mainly at Campus Vaasa. The studies of the programme involve not only theoretical lectures but also practical ways of learning, laboratory assignments and hands-on exercises in innovative learning environments.

The learning process is characterized by a strong integration of real working life problems and development projects. The thesis work is realized as a research and development project related to working life.

Study Content

Novia UAS offers a renewed curriculum from 2024 for the Master’s programme in Intelligent Systems, with a distinct profile in machine learning and artificial intelligence for industrial applications. The curricula include the practical application of machine learning methods for intelligent industrial automation. Both model-based and data-based methods are covered. Specific applications may include automatic quality control, data-driven fault detection, techniques for predictive and forecasting purposes and the study of generative models.

The degree program is linked to the Intelligent Systems Institute at Novia, which focuses on making applied intelligent systems knowledge and recourses readily available for companies.