Syllabus

LEARNING OUTCOMES

The student will get more familiar using python. The course has the following intended learning outcomes:

Reading and writing to files in different formats(Xml,Json,Csv)
Installing, importing and using packages and libraries
Use numpy, panda, scipy and matplotlib.
Get familiar with lambda, zip, map and sort.

Given a specific problem, define the input, calculation and output in pseudo-code
Clean a dataset, perform various calculations (e.g. regression) on data, present findings with appropriate diagrams.
Use vector and matrix calculations and being able to optimize the code for sparse data.
Choose which information to present and how

Credits: 3

Schedule: 27.02.2024 - 10.04.2024

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):

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

Assessment Methods and Criteria

• valid for whole curriculum period:

  The final course grade consists of two parts: Graded weekly programming exercises and a graded group project

Workload

• valid for whole curriculum period:

  Lectures, independent work, group work & exercises

DETAILS

Study Material

• valid for whole curriculum period:

  Lecture material and resources are found on myCourses

Substitutes for Courses

• valid for whole curriculum period:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

FURTHER INFORMATION

Further Information

• valid for whole curriculum period:

  Teaching Language : English

  Teaching Period : 2022-2023 Spring IV
  2023-2024 Spring IV

Description