Decision and Data Science Applications (MOD900)
Course description for study year 2024-2025
Course code
MOD900
Version
1
Credits (ECTS)
10
Semester tution start
Spring, Autumn
Number of semesters
1
Exam semester
Spring, Autumn
Language of instruction
English
Content
Learning outcome
Knowledge:
- Upon completion of the course the PhD candidate should understand the fundamental principles of decision and data science as applied to energy resource engineering as well as understand how principles applies within research. The candidate should have a deep and broad understanding of how to apply these principles to support energy resources related decision making.
Skills:
- Skills needed to build a good basic decision model and to use it in generating powerful insights into the decision situation
- Be able to apply and construct decision models and to use the most important elements in decision analysis relevant to engineering type decision-making in the face of uncertainty.
General competence:
- The PhD candidate should understand fundamental logical principles and analyses and be able to communicate their choices and recommendations clearly.
Required prerequisite knowledge
Exam
Form of assessment | Weight | Duration | Marks | Aid |
---|---|---|---|---|
Portfolio | 1/1 | Passed / Not Passed |
Portfolio assessment:
• Achieve a grade of B or better in one of the courses MOD500, MOD550 or PET685
• Pass a project related to the course to be determined by the PhD student’s advisor