Digital Twins, 6 credits
Start of studies
Autumn semester 2030
Form of education
Campus, Day-time, 2/5
Language
English
Period
2030 week 45 until 2031 week 3
Admission to the course requires 2 completed credits in Applied Machine Learning and 2 completed credits in Systems Engineering. English 6.
The aim of the course is for the student to acquire knowledge and understanding of the digital twin concept. The course provides tools and methods for developing own digital twins of products. The course includes a mix of theory, methods, and tools for digital twins to implement and operate a digital copy of a physical product.
Admission to the course requires 2 completed credits in Applied Machine Learning and 2 completed credits in Systems Engineering. English 6.
Level
A1F
Course code
MT2583
