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Techniques for Large-scale Data

Master's level | 7.5 credits | Course code: DIT872

The course does not start as a freestanding course this academic year but can start within a program or a course package. Please contact the department for further information.

About the Course

The aim of this course is to deepen the students’ knowledge and skills and familiarize them with the technical and technological side of data science, including relevant data models, and software respectively hardware environments. The course will introduce aspects of designing and implementing large-scale data science solutions.

In particular the course will include

  • an overview of computer architectures and high-performance computing infrastructures with a focus on limitations for processing large-scale data,
  • an introduction to relevant frameworks for cluster computing with large-scale data,
  • implementation of data analysis tools on a cluster using Python and appropriate software frameworks,
  • an overview of non-relational database technologies,
  • semantic web and related technologies,
  • an overview of ethical questions regarding large-scale data, e.g. with respect to licenses, accessibility, and anonymisation.

More Information

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Course Syllabus


Tuition Fee

Please contact the department.
EU/EEA citizens, Swedish residence permit holders and exchange students do not pay fees. More information on:

Study Guidance



Department of Computer Science and Engineering
41296 Göteborg

Visiting address: Rännvägen 6 B

Page Manager: Pontus Sundén
Last update: 6/15/2018 12:12 PM

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Page Manager: Pontus Sundén|Last update: 10/16/2018

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