Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.


Credits: 2

Schedule: 18.05.2021 - 24.06.2021

Teacher in charge (applies in this implementation): Barbara Keller

Contact information for the course (valid 07.05.2021-21.12.2112):

Teacher in Charge: Dr. Barbara Keller

Co-Teacher: Mélanie Cambus

Head TA: Visa Mäkeläinen

Zachary Burda
Hyung Jun Chang
Aaron Campbell 

CEFR level (applies in this implementation):

Language of instruction and studies (applies in this implementation):


  • Applies in this implementation:

    Target audience: Everyone who wants to deepen their programming skills by using python to solve engineering tasks and analyze data
    Prerequisites: Basic programming skills similar to the skills from CS-A1113 Basics in Programming Y1 (while and for-loop / if-then-else)

    The course takes 6 weeks and is divided into 3 main components:
    • Reading and Structure (week 1 & 2)
    • Calculations and Functions (week 3 & 4)
    • Results and Presentation (week 5 & 6)

    Some selected learning outcomes:
    • From data given in a CSV file, you are able to tell the min, max and average
    • Given a data set you are able to clean your data for further processing
    • You can explain what regression is and apply it
    • You will be able to present your scientific findings and your data in an appropriate way

Assessment Methods and Criteria
  • Applies in this implementation:

    The course consists of individual exercises and a project. 

    The final grade is a weighted average of 40% of the exercise grades and 60% of the project grade.