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 2 - 404
Consultation hours
- Tuesdays 10.30-12.30, Liivi 2- 119 (Please book an appointment with Email first).
Final Exams
27.05.2019: 10.15-- 13.15: Room 404
03.06.2019: 10.15-- 13.15: Room 122
10.06.2019 (Resit) : 10.15-- 13.15: Room 224
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.
Assessment of the course
There are two modes of assessment. Homeworks (60 marks) and Final Exam (40 marks). To get a pass grade, you must score at least 51 points in total AND at least 16 out of 40 points in the final exam.
Organizers of the course
Marlon Dumas is responsible for this course while Rajesh Sharma will teach 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.