course-details-portlet

VB8000

AI and Digital twin for Engineering

Choose study year
Credits 7.5
Level Doctoral degree level
Course start Autumn 2025
Duration 1 semester
Language of instruction English
Location Gjøvik
Examination arrangement Assignment and oral examination

About

About the course

Course content

Introduce PhD students from various engineering fields to foundational concepts and practical applications of AI and digital twins, highlighting their integration across diverse engineering problems. The course will include

  • Overview of AI techniques and digital twins applied to engineering disciplines, with emphasis on the sustainability.
  • Data management and information flow.
  • Real-world case studies (e.g., predictive maintenance, process optimization).
  • Exploring next steps in AI and digital twin advancements for engineering.

Learning outcome

By the end of the course, students will be able to:

  • Identify opportunities for digital twins and AI in their field.
  • Design basic digital twin or AI models for their own PhD topic.
  • Recognize and address ethical and data-related challenges.

Learning methods and activities

Lectures, colloquia, self studies, preparation of an individual project report. The topic of the report will be related to the research areas covered by the course, and it may be related to the actual PhD project of each student. When there is less than 3 students, the course will designed for mainly self study.

The course can be given online by request.

To have access to exam, students should join 70% of lectures.

Compulsory assignments

  • Seminar

Further on evaluation

For a re-take of an examination, all assessments during the course must be re-taken.

To take the exam, shall students join at least 70% of lecture/seminars

Specific conditions

Admission to a programme of study is required:
Engineering (PHIV)

Required previous knowledge

PhD candidates within research areas related to Engineering.

Course materials

Textbooks, reports, papers, etc. to be announced at the start of the course.

Subject areas

  • Computer and Information Science
  • Engineering

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of Manufacturing and Civil Engineering

Examination

Examination

Examination arrangement: Assignment and oral examination
Grade: Passed / Not Passed

Ordinary examination - Autumn 2025

Oral examination
Weighting 40/100 Examination aids Code E Duration 30 minutes
Approved report
Weighting 60/100 Examination aids Code A Exam system Inspera Assessment