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This is the talk materials repository of the "Use Case Seminars 2." course in the 2024/2025 Spring term, part of the MSc in Business Analytics at CEU. For the previous editions, see 2018/2019 Spring, 2019/2020 Winter, 2020/2021 Fall, 2021/2022 Fall, 2022/2023 Spring, and 2023/2024 Spring.

Course Description

This class is a series of guest talks from industry experts followed by Q&A sessions, where you can learn about real-world data-science questions and problems, then the related solutions, products and teams -- right from the trenches, featuring senior data scientists, data engineers and data team leads from startups and enterprises as well. The examples demonstrated and discussed in these sessions will not only help you with ideas for the cap/final project, but will also show you the different aspects of real-world data science and give you some ideas on what to expect at your future job.

We invite 1-2 experts each week to deliver a case study of a real data science problem and solution, followed up by Q&A and then R exercises related to the discussed case studies.

This is a Pass / Fail class. Students are required to attend all weeks and actively participate in the Q&A and R exercises sessions.

Class Schedule

Apr 28, 30 and May 5, 7, 12, 14 between 17:40 and 19:20 with one or two invited speakers, in most cases in-person, in a few occasions over Zoom.

Invited Talks

  • Apr 28, 2025 (Monday) 17:40 - 17:50 intro

  • Apr 28, 2025 (Monday) 17:50 - 19:20 Levente Otti (Emarsys/SAP)

  • Apr 30, 2025 (Wednesday) 17:40 - 19:20 Tamas Molnar (BT Group)

  • May 5, 2025 (Monday) 17:40 - 19:20 Dora Szabo (shapr3D)

  • May 7, 2025 (Wednesday) 17:40 - 19:20 Stefan Theussl (Raiffeisen Bank International AG)

  • May 12, 2025 (Monday) 17:40 - 18:25 Neal Fultz (freelancer consultant)

  • May 12, 2025 (Monday) 18:30 - 19:20 Szilard Pafka (ML tools)

  • May 14, 2025 (Wednesday) 17:40 - 18:20 Ajay Gopal (Rx Studio)

  • May 14, 2025 (Wednesday) 18:20 - 19:20 Gergely Daroczi (Rx Studio)

Contact

File a GitHub ticket.

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Invited talks on using R for Data Science from industry experts

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