Course - Big Data Architecture - TDT4305
Big Data Architecture
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, self-study and project.
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.
If the course is still not passed after a postponed exam, or by repeating the course, all parts of the course must be retaken.
Recommended previous knowledge
TDT4120 Algorithms and Data Structures and TDT4145 Data Modelling, Databases and Database Management Systems, or equivalent.
Course materials
Will be informed of at semester start.
Subject areas
- Informatics
- Technological subjects
Contact information
Course coordinator
Lecturers
Department with academic responsibility
Examination
Examination
Ordinary examination - Spring 2024
School exam
The specified room can be changed and the final location will be ready no later than 3 days before the exam. You can find your room location on Studentweb.