Level of Study
Objectives and Content
Objectives: The course aims to give knowledge in the selected optimization topics.
Content: The course deals with optimization theory and algorithms. Exact content wil vary from year to year.
On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:
- knows the theory of the selected optimization topics that have been lectured
Required Previous Knowledge
At least 120 ECTS in computer science, preferably including some mathematics
Recommended Previous Knowledge
Good knowledge to optimization.
Access to the Course
Access to the course requires admission to a master¿s programme at The Faculty of Mathematics and Natural Sciences
Teaching and learning methods
The teaching is given in terms of lectures
Lectures / 2-4 hours per week
Forms of Assessment
Final oral exam
Examination Support Material
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Same semester the course is taught, and the subsequent.
The reading list will be available within June 1st for the autumn semester and December 1st for the spring semester
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
Course coordinator and administrative contact person can be found on Mitt UiB, or contact mailto:firstname.lastname@example.org Student adviser
The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.
mailto:email@example.com Student adviser
T: 55 58 42 00
Type of assessment: Oral examination
- Withdrawal deadline