t.BA.DS.DSG.20HS (Data Science Fundamentals) 
Module: Data Science Fundamentals
This information was generated on: 27 September 2021
No.
t.BA.DS.DSG.20HS
Title
Data Science Fundamentals
Organised by
T IDP
Credits
4

Description

Version: 1.0 start 01 August 2020
 

Short description

The course provides an introduction into the fundamental aspects of the data science practice. The students develop an understanding for the technical, ethical and legal challenges in the development of data products. The concepts are implemented in practical use cases.

Module coordinator

Full Name (ZHAW username)

Learning objectives (competencies)

Objectives Competences Taxonomy levels
the students develop a fundamental understanding of the development of data products F, M K1
apply the development process on a given problem statement F, M, SE K1-2
understand the fundamental principles of intangible property rights and data protection and how they affect the development of data products F, M K1
reflect and discuss ethical questions around data products F, M, SO K1-2

Module contents

The students learn the fundamental aspects and the corresponding challenges in the development of data products. They collect first experiences in the incremental procedure consisting of
  • Business Understanding
  • Data Acquisition and Understanding
  • Modelling
  • Evaluation
  • Deployment and integration of the product
  • Collection of user feedback
The concepts are applied in an accompanying project. The practical work involves basic analytics tools, such as text editor Microsoft Excel, and a No Code-environment for machine learning applications. Furthermore, the course covers ethical and legal challenges associated with the processing of data and the development of data products.
Basic knowledge in mathematics and logical thinking are required, but no programming knowledge is required.

Teaching materials

Presentation material, work sheets

Supplementary literature

Applied Data Science: Lessons Learned for the Data-Driven Business; Stockinger Kurt, Braschler Martin and Stadelmann Thilo, Ed. Cham: Springer International Publishing, 2019

Prerequisites

 

Teaching language

(X) German ( ) English

Part of International Profile

( ) Yes (X) No

Module structure

Type 3a
  For more details please click on this link: T_CL_Modulauspraegungen_SM2025

Exams

Description Type Form Scope Grade Weighting
Graded assignments during teaching semester Project Report Written 1 Report Graded 20 %
End-of-semester exam Exam Written 90 Minutes Graded 80 %

Remarks

 

Legal basis

The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.
Course: Data Science Grundlagen - Praktikum
No.
t.BA.DS.DSG.20HS.P
Title
Data Science Grundlagen - Praktikum

Note

  • No module description is available in the system for the cut-off date of 02 August 2099.
Course: Data Science Grundlagen - Vorlesung
No.
t.BA.DS.DSG.20HS.V
Title
Data Science Grundlagen - Vorlesung

Note

  • No module description is available in the system for the cut-off date of 02 August 2099.