Databases and Data Mining
- Yes Elective choice
- No Contractonderwijs
- Yes Exchange
- Yes Study Abroad
- No Evening course
- No A la Carte
- No Honours Class
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.
|Is part of||Programme type||Semester||Block|
|Astronomy and Data Science||Master||1|
|Computer Science: Bioinformatics||Master||1|
|Computer Science: Computer Science and Advanced Data Analytics||Master||1|
|Computer Science: Computer Science and Business Studies||Master||1|
|Computer Science: Computer Science and Education||Master||1|
|Computer Science: Computer Science and Science Communication and Society||Master||1|
|Computer Science: Data Science||Master||1|