course-details-portlet

TDT4305

Big Data Architecture

New from the academic year 2015/2016

Credits 7.5
Level Second degree level
Course start Spring 2016
Duration 1 semester
Examination arrangement Portfolio assessment

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, Storm, etc.) NoSQL databases, mining Big Data, data streams and analysis of time series, and social network analysis.

Learning outcome

Knowledge: The candidate will get knowledge of:
- Big Data frameworks.
- Mining of Big Data.
- Processing of data streams.
- Analysis of time series.
- 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, seminars and project. Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written test (75%) and project or seminar (25%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. 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

Examination

Examination

Examination arrangement: Portfolio assessment
Grade: Letters

Re-sit examination - Summer 2016

Arbeider
Weighting 25/100
Oral examination
Weighting 75/100 Date 2016-08-08

Ordinary examination - Spring 2016

Arbeider
Weighting 25/100
Skriftlig eksamen
Weighting 75/100 Date 2016-05-28 Time 09:00 Duration 4 timer Place and room Not specified yet.

All about examinations at NTNU