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Introduction to intelligent systems (5 cr)

Code: INS24IS01-3001

General information


Enrollment

15.06.2024 - 22.09.2024

Timing

25.08.2024 - 31.12.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Faculty of Technology and Seafaring

Campus

Vasa, Wolffskavägen 33

Teaching languages

  • English

Degree programmes

  • Degree Programme in Intelligent Systems

Teachers

  • Ray Pörn
  • Johan Westö

Teacher in charge

Ray Pörn

Groups

  • IS24H-V
    Intelligent Systems, 2024, part-time studies

Objective

The students will be introduced to intelligent systems in the industrial context. The student will learn what defines an intelligent system and the basic principles of intelligent systems. The student will gain knowledge of the parts that constitute an intelligent system and how they interact.

After completing the course, the student should be able to:
Knowledge and understanding
- explain the basic parts and functionality of an intelligent system
- describe the challenges, risks, and opportunities with intelligent systems
- understand the working principles of intelligent systems

Skills and abilities
- analyze the needs and requirements for an intelligent system
- practice with different methods for realizing intelligent systems

Evaluation ability and approach
- plan the development of an intelligent system
- propose and evaluate solutions for intelligent systems

Content

Content
The course gives an overview of intelligent systems in the industrial automation context. The course serves as a common platform of knowledge for the studies in the program. Content:
• Fundamentals of industrial automation systems
• Data-driven and model-based design
• Automated and autonomous decision making
• Digital twins
• Sensors and IoT devices
• Data collection, storage, and flow
• Cyber security

Materials

The study material will be provided by the lecturer.

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

Grade 1: Satisfactory skills in understanding and development of intelligent systems.

Assessment criteria, good (3)

Grade 3: Good skills in understanding and development of intelligent systems.

Assessment criteria, excellent (5)

Grade 5: Excellent skills in understanding and development of intelligent systems.

Qualifications

No prerequisites.