ITEVU4130 – Digital Twins for Science and Applications

Course content

This course introduces the digital twin as an integrating framework for data and computational science, and introduces the concept of the digital twin and discusses its history and relationship to data science.

It also presents the architectural elements of a digital twin, such as sensor information that is fused with modelling and static information about a system to support decisions, and introduces core scientific topics needed for digital twins such as semantic representation, model identification and assimilation, dynamics and handling of time-series data, and decision support using digital twins. The course examines examples from industry, science and smart cities, and allows hands-on work with time-series data from real industrial processes.

Learning outcome

After completing this course you will:

• understand and be able to describe the role of a digital twin as an integrating framework for digitalization and data science.
• be able to know and use important architectural and project models for digital twins.
• understand the linkage between digital twins, machine learning and artificial intelligence.
• be able to understand and evaluate different modelling approaches in digital wins.
• be able to write a feasibility study for a digital twin application.

Admission to the course

In order to take the course, Higher Education Entrance Qualification is required. In addition, it is assumed that applicants have a professional educational maturity corresponding to a bachelor's degree in science. Some EVU-courses will also require or build on certain prior knowledge in order for participants to fully benefit from the teaching. Although such prior knowledge is not a requirement for admission, we would advise against applying for courses where you lack recommended prior knowledge. For those courses where this is relevant, it will be stated in the course description.

Apply for admission

1. The link above will direct you to the admission portal EVUweb.
2. Choose "University of Oslo" as institution.
3. Click on "Register application".
4. Log in with ID-porten, Feide eller eIDAS.
5. Add or change user information and create user.
6. Follow the instructions of the application form and submit application.

Formal prerequisite knowledge

Higher Education Entrance Qualification

Minimum 2 years of relevant professional experience.

Teaching

Three one-day sessions, each of three hours seminar and two hours practical and workshop activities.

Examination

Project assignment which counts 100 % towards the final grade.

When writing a project assignment make sure to familiarize yourself with the rules for use of sources and citations. Breach of these rules may lead to suspicion of attempted cheating.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.