Data Science Seminar: Data Science for Business Optimization

Rapid advances in data science and artificial intelligence have opened numerous avenues for optimizing business operations. Virtually every industry and every business process is being transformed by these rapid developments. This seminar will showcase case studies and experiences on the use of data science and AI to increase customer engagement, improve customer experience, and enhance efficiency and quality, across various industries.

The seminar will cover two complementary perspectives: the problem-driven perspective and the solution-driven perspective. Along the first perspective, we will discuss how a given data science method can be applied to tackle certain classes of business optimization problems, like applying process mining to discover root-causes of delays, or using recommender systems to improve customer engagement. Along the second perspective, we will discuss how to tackle a given business optimization problem (e.g. increasing sales without increasing capacity) using one or more data science methods.

Agenda:
16:45 Gathering & welcome coffee
17:00 Introduction by the moderator
17:05 Marlon Dumas (University of Tartu) – Data science and AI for business process improvement
17:40 Markus Lippus (MindTitan) – The unexpected use cases for a machine that can listen
18:10 Coffee break
18:30 Sven Laur (STACC) – Health insurance analytics: A case study at the Estonian Health Insurance Fund
18:55 Lauri Antalainen (CoreGrow) – Optimizing production processes: how can data science help?
19:15 Panel discussion

Participation is free of charge, but registration is needed. NB! Marking yourself as “Going” on Facebook does not count as registration. Register here: https://forms.gle/GfRcZjLWr2HrsrFm6

The seminar will be held in English. Limited amount of seats available. Information and recordings from previous seminars are available: https://www.cs.ut.ee/…/industry…/data-science-seminars

This event is supported by the University of Tartu ASTRA project PER ASPERA Doctoral School of Information and Communication Technologies