Scientific Programming

Course content

The course introduces scientific programming with the Python programming language and addresses problem solving, organization and visualization of data, file organization and scripting, numerical computing, supervised learning, graphs, information retrieval, and neural networks.


Learning outcome

The student is able to:

  • program with linear algebra
  • implement routine procedures relevant to data managing
  • create plots or related visualisations of data
  • implement simple learning algorithms or related algorithms of importance to cognitive technologies


See the curriculum:

Lectures and exercise classes

7,5 ECTS
Type of assessment
Active student participation consisting of 3-5 assignments
Marking scale: passed/not passed
Marking scale
passed/not passed
  • Category
  • Hours
  • Class Instruction
  • 56
  • Course Preparation
  • 105
  • Exam Preparation
  • 45
  • English
  • 206