Altair Data Science Day

November 2, 2023 | 10:00 AM to 12:50 PM CET (Session 1) and 5:00 to 7:50 PM CET (Session 2)

Exploring code-free and code-friendly learning and teaching

Join our event to understand how others in the Altair RapidMiner community have leveraged this tool’s broad applicability to make more informed, data-driven decisions – by including data science and analytics in numerous university and open online courses pertaining to a wide range of domains such as business, finance, science, healthcare, and engineering.

Follow presentations and discussions on how the low-code approach of Altair RapidMiner facilitates the education of novices in data science with a low barrier to entry. Hear from Altair leaders regarding the present and future focus on using the RapidMiner platform for Engineering Data Science.

For your convenience, the event will take place in two time zones. All presentations will be in English.


Who should attend?

This event is for anyone wanting to complement their learning and/or teaching of data science by using Altair RapidMiner. No matter if you are a new or existing professor already teaching with RapidMiner, a university student wanting to learn data science to be better prepared for a future job, or if you are working in industry and seeking ideas for what is possible with RapidMiner in your domain.

Why should I attend?

  • Connect with and become part of the global Altair RapidMiner community with 1M+ users and growing
  • Explore ways to develop your own skills with RapidMiner to become a more proficient citizen data scientist
  • Know how to access and make good use of academic resources available, especially for course instruction
    to help your students and learners effectively gather insight from data and use it to positively shape the future
  • Interact with data science course instructors and Altair experts worldwide
  • What is RapidMiner?

    Altair RapidMiner is a code-free and code-friendly platform for Data Science, Artificial Intelligence (AI), and Machine Learning (ML).