TIES438 Big Data Engineering (5 op)
Kuvaus
Content
During the course multiple facets related to the Big Data phenomenon will be studied. First, students will get introduced to large data sets and streaming data. Then, example storage solutions and processing algorithms will be studied. Finally, we will look into hardware considerations and apply the theory on real world datasets related to news, wikipedia, brain analysis, biology, chemistry, etc.
Students who wish to work on a problem specific to their own research should discuss this with the teacher at the beginning of the course.
Completion methods
The course is completed by implementing the assigned tasks. A small part of the evaluation is done by quizzes during the lectures.
Assessment details
The implementation of algorithms is intended to assist the students in their understanding of the course content.
Osaamistavoitteet
Lisätietoja
Esitietojen kuvaus
Oppimateriaalit
Kirjallisuus
- Motwani, and Raghavan. Randomized Algorithms. Cambridge, UK: Cambridge University Press, 1995. ISBN: 0521474655. (available in JYU trough EBSCOhost https://jyu.finna.fi/Record/jykdok.1485577 ); ISBN: 0521474655
- Mining massive data sets - Anand Rajaraman, Jure Leskovec, Jeffrey D. Ullman free download from http://www.mmds.org/
- https://jyu.finna.fi/Record/jykdok.1485577
- http://www.mmds.org/