LEARNING OUTCOMES
Credits: 3
Schedule: 01.03.2022 - 12.04.2022
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Barbara Keller
Contact information for the course (applies in this implementation):
Credits: 3
Schedule: 01.03.2022 - 12.04.2022
Teacher in charge (applies in this implementation): Barbara Keller
Contact information for the course (valid 01.03.2022-12.04.2022):
Teacher in Charge: Dr. Barbara Keller
Head TA: Visa Mäkeläinen
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
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 dataPrerequisites: Basic programming skills similar to the skills from CS-A1113 Basics in Programming Y1 (while and for-loop / if-then-else)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.
Workload
applies in this implementation
The course takes 7 weeks and is divided into 3 main lecture components and the presentation of the group project:- Reading and Structure (week 1 & 2)
- Calculations and Functions (week 3 & 4)
- Results and Presentation (week 5 & 6)
- Group project presentation (week 7)
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period: