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t.BA.DS.DSG.20HS (Data Science Fundamentals)
Module: Data Science Fundamentals
This information was generated on: 25 October 2024
No.
t.BA.DS.DSG.20HS
Title
Data Science Fundamentals
Organised by
T IDP
Credits
4
Description
Version: 2.0 start 01 August 2024
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
K1-2
apply the development process on a given problem statement
F, M, SE
K3
understand the fundamental principles of intangible property rights and data protection and how they affect the development of data products
F, M
K1-3
reflect and discuss ethical questions around data products
F, M, SO
K1-3
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.
Note
Additional available versions:
1.0 start 01 August 2020
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.