t.BA.DS.OSI.20HS (Operating Systems and Infrastructure) 
Module: Operating Systems and Infrastructure
This information was generated on: 24 July 2024
Operating Systems and Infrastructure
Organised by


Version: 3.0 start 01 August 2023

Short description

Efficient use of data and computationally-intensive applications requires basic operating system concepts to be understood. Operating systems also provide many tools for basic data processing and automation through shell scripts. Students use remote virtualised infrastructure and services for data processing, creating and linking data science services to run data- or computationally-intensive applications.

Module coordinator

Josef Spillner (spio)

Learning objectives (competencies)

Objectives Competences Taxonomy levels

You understand basic concepts of modern operating systems.

F,M K2

You are able to use the shell and tools of the operating system to process data and automate processes.

F,M K3

You understand the virtualization mechanisms of operating systems and can apply them in practice.

F,M K3

You know the different operating models for infrastructure and data processing services and can decide which are most suitable for your application.

F,M K3

You can build cloud infrastructure and services automated and utilize them for data processing.

F,M K3

Module contents

Operating systems and tools:

  • Basic concepts of modern operating systems (especially resource management, process management and file system)
  • How to work with the operating system shell. Using operating system tools, implementing pipelines and simple shell scripts to automate data processing tasks.
  • Principles of hardware and operating system virtualization and their application in data processing. Using virtual machines and containers on the local computer and in the data-centre.
  • Interaction between programming language and operating system.

Infrastructure for data- and computing-intensive applications:

  • Version control, data integration and workflows.
  • Cloud computing as well as cloud services for data processing.
  • Usage of cloud services to create data processing workflows (event-based processing, pipelines, DataOps/MLOps, ...)
  • Automated provisioning of data processing services as well as reproducibility of the processing.

Teaching materials

Lecture book/script
Lecture videos
Slides on selected topics
Shell usage transcripts

Supplementary literature



Python programming (XXI.PROG1 & 2)

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


Description Type Form Scope Grade Weighting
Graded assignments during teaching semester Control questions in the form of challenges and one project written (electronic) per topic; 20-30 minutes Grade 20%
End-of-semester exam Exam written (electronic) 90 minutes Grade 80%



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: Operating Systems - Praktikum
Operating Systems - Praktikum


  • No module description is available in the system for the cut-off date of 02 August 2099.
Course: Operating Systems und Infrastruktur - Vorlesung
Operating Systems und Infrastruktur - Vorlesung


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