Robust intelligent systems

During this module of methods and technologies for robust intelligent systems the student will learn theoretical concepts of machine learning algorithms and methods for data classification, clustering and projection. The student also learns methods for fuzzy logic, neural networks, soft computing, evolutionary algorithms and their applicability to energy technology applications in particular. The student gets familiar with concepts of cryptography, types of cyber security threats in distributed systems and IoT, and to identify weak points and protect typical embedded systems.

In addition, the student can choose a course with a learning outcome of

  1. being able to select sensors for control applications,
  2. learning about smart IT devices of electrical engineering or
  3. gaining deeper knowledge of the tools for cyber security management.

In the module, there are three (3) compulsory courses:

Machine learning (ICAT3120), 5 ECTS
Artificial intelligence in energy technology (ICAT2090), 5 ECTS
Security of embedded and distributed systems (ICAT3160), 7 ECTS

Student chooses one of the following courses to strengthen their competence:

Sensor and control technology (ICATC2010), 5 ECTS
Energy technology ICT (ICATC2030), 5 ECTS
Management of cyber security (TITE3370), 5 ECTS

Courses included in the programme:

= Contact learning
= Online learning
= Blended learning (online & contact learning)
Energy technology ICT (ICATC2030), 5 ECTS. Autumn 2019.

Course level: Intermediate.

Prerequisites: Courses Introduction to Programming and/or Physical Principles of Energy Technology or equivalent information.

This course contains learning the concept of smart grid as well as the principles and communication methods of IT devices used in electrical distribution, protection and control.


  • Smart grid, ICT systems of electrical distribution and invoicing.
  • Smart IT devices of electrical engineering, such as the protection relay and the frequency converter.
  • Communication protocols used in distributed energy production.
  • Basic principles of the standard IEC61850.
  • New services, which are made possible by smart grids.

Responsible teacher: Timo Mantere (timo.mantere(at)

Artificial intelligence in energy technology (ICAT2090), 5 ECTS. Spring 2020.

Course level: Intermediate.

Prerequisites: It is highly recommended to know basics of programming. Also some knowledge on object-oriented programming is recommended.

On this course, students will learn the principles of fuzzy logic, rules and control, evolutionary computation, multiparameter and global optimisation as well as basics of neural networks. The idea is to learn how to apply these theoretical methods to energy applications. Content also includes different soft computing methods and designing, implementing and testing simple soft computing applications.

More information on University of Vaasa’s WebOodi page.

Responsible teacher: Jarmo Alander (jarmo.alander(at)

Sensor and control technology (ICATC2010), 5 ECTS. Spring 2020.

Course level: Intermediate.

Prerequisites: Courses Sulautettujen järjestelmien perusteet, Ohjelmistotestaus or equivalent information.

After completing the course, the student are able to

  • describe and analyse dynamic control systems and feedback control mathematically
  • describe the main principles and features of basic control algorithms
  • select sensors for control applications
  • learn about the importance of control technology especially in the energy industry
  • design and implement a dynamic control system.

Responsible teacher: Timo Mantere (timo.mantere(at)
Other teachers: Santiago Chavez, Jukka Matila, Janne Koljonen

Security of embedded and distributed systems (ICAT3160), 7 ECTS. Autumn 2019.

Course level: Advanced.

Prerequisites: It is highly recommended to know: embedded system architecture, and embedded C programming.

On this course, the student will learn about the different concepts of cryptography and what types of cyber security threats exist in distributed systems. The course will also focus on identifying the weak points of embedded systems, how embedded systems are usually attacked (with practical examples), how to protect embedded systems, how to to apply cryptographic algorithms and the concept of ”trusted computing”.

Responsible teacher: Mohammed Elmusrati (mohammed.elmusrati(at)
Other teachers: Tobias Glocker (tobias.glocker(at)

Machine learning (ICAT3120), 5 ECTS. Spring 2020.

Course level: Advanced.

Prerequisites: It is highly recommended to know fundamentals of probability theory and university level calculus.

NB! The course is organised once a year in spring. However, it is possible to arrange the course also as self-study with few hours of online meetings. For self-studying, the course could be arranged also in autumn.

Max amount of FITech students: 15

The main concepts as well as the different types of machine learning are covered on this course. The approach of this course is to cover machine learning from algorithmic point of view. The aim of this approach is to understand the theories/algorithms behind machine learning algorithms and how to select the best one for our specific problem, to know their limits, and even how to modify it to fit our specific problem

This course is highly useful wherever there is data to be analysed. Hence, the application area is huge either in industry, factories, power plants, social science, business, finance, etc.

It is important that the student has good mathematical background as well as some programming skills (in any programming language) in order to to maximise the gained knowledge.

More information on University of Vaasa’s WebOodi page.

Responsible teacher: Mohammed Elmusrati (mohammed.elmusrati(at)

Management of cyber security (TITE3370), 5 ECTS. Spring 2021.

Course level: Advanced.

The course is organised according to lectures’ schedule. Attendance is not mandatory since lectures are also recorded.

This course targets advanced knowledge about cybersecurity and its domains.

After the course, the student recognises the need for cybersecurity measures and has the knowledge of the techniques and methods to bring them into place. The student understands about the information assurance fundamentals (CIA +  Parker + ISO), cryptography techniques, operating systems and application security, threats, vulnerabilities and attacks, security models, security analysis and design, risk management and risk mitigation, physical security, compliance, standards, policies and best practices, cybersecurity frameworks, and finally the main authority organisations.

On the course, there will be co-operation with Wärtsilä, ABB, VEO, Elisa Santa Monica, Verizon and others.

More information on University of Vaasa’s WebOodi page.

Responsible teacher: Tero Vartiainen (tero.vartiainen(at)
Other teachers: Bahaa Eltahawy, Duong Dang

Further information

Academic coordinator: Maria Tuuri (maria.tuuri(at)

Type of study unit

Set of courses


5–22 ECTS

Teaching semester


Host university

University of Vaasa

Open for degree student


Open for non-student


Level of studies

Intermediate & advanced

Teaching methods

Contact or online learning

Place of contact learning


Programme suitable for




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