|Period:||period 1 (week 36 through 45, i.e., 2-9-2019 through 8-11-2019; retake week 1 (bachelor) / 2 (master))|
|Participants:||up till now 154 subscriptions|
|Schedule:||Official schedule representation can be found in MyTimetable|
|Note:||No up-to-date course description available.|
Text below is from year 2018/2019
|Contents:||For questions about enrollment, registration, waiting lists,
admittance, etc. please contact the student desk at email@example.com.
Note: basic knowledge of probability, statistics and calculus is
The following subjects are discussed:
Lecture notes and selected articles/book chapters.
|Course form:||Lectures and Computer Lab.|
|Exam form:||Written exam and practical assignments.|
|Minimum effort to qualify for 2nd chance exam:||To qualify for the retake exam, the grade of the original must be at least 4.|
The amount of data that is produced and stored by companies and other organizations is still growing every day.
Examples of problems that data mining can help address are:
In this course we study a number of well-known data mining algorithms. We discuss what type of problems they are suited for, their computational complexity and how to interpret and apply the models constructed with them.