Description
This course is meant for students as a hands-on experience for solving business problems in the fields of sales, marketing, and business operations by applying statistical analysis and data mining techniques.
We will be using R to handle the case studies. Before the first lecture, please, download R https://cran.r-project.org/ and RStudio https://www.rstudio.com/.
Schedule
- Mondays 10:15-13:45, Liivi 4-105
Consultation hours
- Tuesdays 10.30-12.30, Liivi 2-119
Exams
- 07.06.2018, 10:15-13:15, room: Juhan Liivi 4, 105
- 11.06.2018, 10:15-13:15, room: Juhan Liivi 4, 105
Organization of the course
Each lecture is 4 academic hours, where in the first 2 hours we learn and discuss the problem, relevant techniques, and solutions, while the next 2 hours are practical, where we solve the case studies. The homework will be mostly the continuation of the provided cases. For homeworks, you can work in a pair or individually. In each class, you will also be ask 1) quiz questions (based on the material being discussed in the class) and 2) class assignments (questions based on a previous class), which will 5 point each. Each student will be picked randomly and each student will get 2 turns in the whole semester.
Final exam will be of 50 marks, out of which you must score atleast 20 marks to clear the course (irrespective of your score in homeworks + quizes + class assignments).
Organizers of the course
Marlon Dumas will give the last lecture on Business Process Mining, while Rajesh Sharma will handle the rest of the course.
For any questions please send an email: rajesh.sharma@ut.ee
Acknowledgment
This course has been developed with the support of the SoBigData Research Infrastructure funded by the European Commision's H2020 Framework Programme.