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 students' website.
Mode of instruction
Panel presentations and discussions.
Hours of study: 168 (= 6 EC)
Practical work: 40
Other (Self-study): 80
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 courses and exams (including retakes) in uSis. Check this link for information about how to register for courses.
Lecturer: dr. Erwin Bakker
Website: Databases and Datamining