The course Databases & Data Mining consists of a series of lectures in which advanced database and data mining techniques will be discussed, with applications to bioinformatics.
At the end of the course, students:
- Should have a clear understanding of the current challenges and state of the art of databases and data mining.
- Will have an understanding of the basic algorithms for preparing data and databases for data warehousing and data mining.
- Will understand the basic data structures and organization that enable data analysis and data mining huge data sets.
- Have an understanding of the important algorithms and challenges in several important emerging applications of data mining: mining biosequence databases, social networks, and graph mining.
The most recent timetable can be found at the LIACS website
Mode of instruction
- Panel presentations and discussions.
“There will be a total of 4 database- and data mining assignments and a final exam (open book). The assignments
P1 and P2 should both be passed with a ‘good’. Subsequently, the final grade will be based on a weighted average
of the grades obtained for assignments P3, P4 and the Exam (E >5): Final Grade = (P3 +2*P4 + 3*E)/6.”
J. Han, M. Kamber, J. Pei. Data Mining Concepts and Techniques (3rd Edition), Morgan Kaufman Publishers, July 2011 (ISBN 978-0123814791)
You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.
Study coordinator Computer Science, Riet Derogee