Course - Big Data - INFT2003
Big Data
Choose study yearAbout
About the course
Course content
Business value of big data. Content, capabilities and applications of big data. Introduction to big data techniques and programming.
Learning outcome
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.
- is familiar with big data architecture.
- 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.
Learning methods and activities
Lessons, video and exercises
Further on evaluation
The portfolio consists of exercises that are approved during the semester. All exercises must be approved to get the portofolio PASSED.
In the event of voluntary repetition, fail (F) or valid absence, the entire portfolio must be retaken in a semester with teaching.
Specific conditions
Admission to a programme of study is required:
Computer Science - Engineering (BIDATA)
Information Technology (ITBAINFO)
Recommended previous knowledge
Some programming experience is an advantage
Course materials
Stated at the start of the semester
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| DIFT2006 | 7.5 sp | Autumn 2020 |
| IINI3012 | 5 sp | Autumn 2020 |
| IFUD1123 | 7.5 sp | Autumn 2020 |
| IT6208 | 7.5 sp | Autumn 2021 |
Subject areas
- Computer Science