Studieprogram

Programme structure

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Showing programme structure for students starting 2019

Study year: 1

Semester: autumn

Programme variant: Obligatoriske emner
Emne ECTS
Examen philosophicum 10 Choose at least one Ex. Phil
Examen Philosophicum - Seminar 10 Choose at least one Ex. Phil
Calculus 1 10 Compulsory Course
Principles of Information Processing 5 Compulsory Course
Introductory Project 5 Compulsory Course

Semester: spring

Programme variant: Obligatoriske emner
Emne ECTS
Mechanics 10 Compulsory Course
Calculus 2 10 Compulsory Course
Programming and Data Processing 10 Compulsory Course
Study year: 2

Semester: autumn

Programme variant: Obligatoriske emner
Emne ECTS
Thermophysics and Electromagnetism 10 Compulsory Course
Linear Algebra and Linear Differential Equations 10 Compulsory Course

Semester: spring

Programme variant: Obligatoriske emner
Emne ECTS
Introduction to data analysis 10 Compulsory Course

 

Detailed description

Social relevance:

Computer sciences will have a huge impact on social development and businesses in the years to come. This study programme gives you the correct tools to find patterns in an abundance of data, and the knowledge to understand and utilize it.

Learning outcomes:

Learning outcomes

  • Upon completion, the candidates should be able to convey and communicate engineering related problems and solutions to both specialists and non-professionals.
  • Be able to contribute to innovation and entrepreneurship.
  • Complete an independent project, restricted to engineering related research- or development under supervision.

Knowledge:

  • Understand the engineering science¿s overall role in a societal perspective, show insight into ethical requirements and respect to sustainable development, and be able to analyze ethical problems regarding engineering related work.
  • Have a broad knowledgebase in mathematics, natural sciences, technology and computer technology as a foundation for understanding methods, applications, professional innovation and adaptations.
  • Have deep knowledge in a defined area connected to active research, including an adequate professional understanding in using new research.
  • Knowledge of computer safety, law and ethics.

Skills:

  • Be able to develop overall solutions to engineering related problems, including creating solutions in a multidisciplinary context. Be able to evaluate tools for analyzing, methods, technical models, calculations and solutions independently and critically.
  • Plan and bring about data collection, as well as process, analyze and interpret the data. Collect and organize data, execute a multivariate analysis of high-dimensional data, pattern recognition and machine learning, evaluate the quality of data as well as the results.
  • Be able to analyze mathematical models for processes e.g. in physics, biology, technique

Qualifications after graduation:

Computer science is in demand and has emerged as one of the futures most important new sciences. The job market is already very lucrative! A qualified workforce within everything from process industry, robotics, telecommunications and energy to banking, insurance, medicine and the consulting industry is in demand.

Contents and structure:

Programme contents and structure

All students must take the following courses:

  • Introduction course 10 credits
  • Examen Philosophicum 10 credits
  • Mathematics 30 credits
  • Informatics 10 credits
  • Physics 20 credits
  • Statistics 10 credits
  • Economics and Social studies 10 credits
  • Informatics- and Computer-Science 60 credits
  • Specializations, including project assignments and a master thesis in applied Computer-Science 120 credits

Evaluation:

Some courses have a written examination, while others have an oral examination. Grades (A-F) are mostly used, but also passed/failed in some courses. Other courses have a longitudinal evaluation, where several components make up the foundation for the final grade. In the final part of the programme, the students will do an independent assignment that shall show their understanding, reflection and maturity.

Cooperation with other institutions:

Arrangements, incoming exchange students:

Admission requirements:

Higher Education Entrance Qualification + SIVING. The study program is taught in Norwegian and applicants who do not have Norwegian, as their native language must document sufficient Norwegian skills to be admitted.

Learning activities:

The programme includes the following methods:
  • Lectures
  • Project assignments, e.g. semester assignment presented to the class
  • While working on their master thesis, joint meetings are arranged where the students present their work
  • Demonstrations
  • Group work in relation to topics, methods, computer-models
  • Exercises from previous exams or other relevant assignments
  • Laboratory analyses
  • Seminar participation
  • Excursions and study trips

Studies abroad:

A study abroad period can be included in the third or fourth academic year.

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