Institute of Computer Science
  1. Courses
  2. 2019/20 spring
  3. Business Data Analytics (MTAT.03.319)
ET
Log in

Business Data Analytics 2019/20 spring

  • Main
  • Lectures
  • Practice sessions
  • Homework
  • Links

Lectures

  1. 10.02 -- Introduction
    • Slides || Video
  2. 17.02 -- Descriptive analysis and visualization
    • Slides || Video
  3. 24.02 -- No Lecture
  4. 02.03 -- Customer segmentation
    • Slides? || Video?
  5. 09.03 -- Customer Lifecycle management - regression problems
    • Slides? || Video?
  6. 16.03 -- Customer Lifecycle management - classification problems
    • Slides? || Video?
  7. 23.03 -- Evaluation of Model's Quality
    • Slides? || Video?
  8. 30.03 -- Cross-sell/Up-sell recommendations: MBA, Collaborative Filtering and Content Based Filtering
    • Slides? || Video?
  9. 06.04 -- Cross-sell/Up-sell recommendations: Neural Networks and Embedding based approach.
    • Guest Lecture by Tiit Sepp (Data Analyst, STACC: Software Technology and Applications Competence Center)
  10. 13.04 -- A/B testing in marketing
    • Slides? || Video?
  11. 20.04 -- Uplift Modeling
    • Slides? || Video?
    • Guest Lecture from Elizaveta Lebedeva (Bolt) Slides? || Video?
  12. 27.04 -- Fraud Detection
    • Slides? || Video?
    • Guest Lecture from Kristjan Eljand (Technology Scount, Eesti Energia) Slides? || Video?
    • Guest Lecture by Christian Safka (Data Analyst, Microsoft)
  13. 04.05 -- Reinforcement Learning + Recommendation Systems
    • Slides? || Video?
    • Guest Lecture from eAgronom Slides? || Video?
  14. 11.05 -- Knowledge Graphs
    • Slides? || Video?
  15. 18.05 -- Fairness and Explainability
    • Slides? || Video?
    • Guest Lecture by Telia
  16. 25.05 -- Business Analytics in Practice: The Case of Swedbank (guest lecturer: Veronika Plotnikova)
  • Institute of Computer Science
  • Faculty of Science and Technology
  • University of Tartu
In case of technical problems or questions write to:

Contact the course organizers with the organizational and course content questions.
The proprietary copyrights of educational materials belong to the University of Tartu. The use of educational materials is permitted for the purposes and under the conditions provided for in the copyright law for the free use of a work. When using educational materials, the user is obligated to give credit to the author of the educational materials.
The use of educational materials for other purposes is allowed only with the prior written consent of the University of Tartu.
Terms of use for the Courses environment