DIFT2006

Big Data

Autumn

Trondheim

Norwegian

Overview

45 candidates

Pass rate

100%

same

Grade distribution
Average over time
Pass rate over time

About this course

Content

Business value of big data. Content, capabilities and applications of big data. Introduction to big data techniques and programming.

Learning outcomes

Knowledge (kunnskaper)

The candidate:

  • understands business value of big data.
  • knows about content, capabilities and applications of big data.
  • knows about techniques for analysis and visualization of big data.
  • understands privacy and trust issues in big data.

Skills (ferdigheter)

The candidate:

  • can articulate and communicate with stakeholders the business value of big data.
  • can structure the process of big data analytics and compose big data analytics teams.
  • can propose and use relevant big data techniques in practical projects.

General competence (generell kompetanse)

The candidate:

  • has an understanding of the significance of big data in companies and society at large.
  • can take part in planning and implementation of big data projects.
  • can identify, plan and implement individual tasks in big data projects.

Teaching methods

The teaching of the course consists of theory followed by practical problem solving. In addition, it is planned that the students will apply the competence they acquire in exercises.