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.

 

Education

IT & Cognition

Learning outcome

Academic objectives

See the curriculum:

MA-level 

2015 curriculum
2019 curriculum


See all the curriculums.

Lectures and exercise classes

Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)
ECTS
7,5 ECTS
Type of assessment
Course participation
Active student participation. The active participation consists of 3-5 written assignments, 6-10 standard pages in total.
Marking scale
passed/not passed
Censorship form
No external censorship
  • Category
  • Hours
  • Class Instruction
  • 42
  • Preparation
  • 105
  • Exam Preparation
  • 59
  • English
  • 206