course-details-portlet

TDT4305

Big Data Architecture

Choose study year
Credits 7.5
Level Second degree level
Course start Spring 2025
Duration 1 semester
Examination arrangement School exam

About

About the course

Course content

The course gives an overview of main aspects of Big Data. Central topics are frameworks for Big Data processing (MapReduce, Spark, Storm, etc.), mining Big Data, data streams, recommender systems, and social network analysis.

Learning outcome

Knowledge: The candidate will get knowledge of: - Big Data frameworks - Mining of Big Data - Processing of data streams - Recommender systems - Analysis of social networks. Skills: - Understand important aspects of Big Data - Ability to apply acquired knowledge for understanding data and select suitable methods for processing and analyzing Big Data.

Learning methods and activities

Lectures and exercises.

Compulsory assignments

  • Exercises

Further on evaluation

The exam is given in English.

If there is a re-sit examination, the examination form may change from written to oral.

Course materials

Will be informed of at semester start.

Other pages about the course

Subject areas

  • Informatics
  • Technological subjects

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of Computer Science