Data Science Cafe - December

In this new edition we have some twists that you probably would like:

· Mentor sections:

• Anita Graser: - GIS
• Kerstin Voglauer - Data Integration
• Lukas Madl - Trustworthy AI - Innovation and Ethics
• Georg Heiler - Governance and pipelines in the modern data stack
• Christopher Kittel - DevOps for NLP & ML
• Maria Ines Plaza - Data4Autism - Data Science hands-on experience. This month focus on production-ready shiny Apps.
• Michal Domanski UX Mentor because almost every Data Science project has UX elements.

· Data4Autism: Here you can explore 4 challenges of solutions that can be implemented using Data Science to help children and people that live with Autism condition. If you are quite knowledgeable about Data Science and now you want to challenge yourself, join this section and go from the idea to the product with the guidance of another Data Scientist and the mom of an autistic child.

The challenges are:
- Speech to Pictogram
- Music composition app to promote verbality
- From goal to Data and back again - Backbone to developmental interventions.
- Emotional Duolingo.

Not interested in any of these options, no problem. There is always space like our traditional event to join other colleagues and choose your own topic.

Everyone is welcome to come and share their own ideas, or simply explore and decide if there is a project you want to be involved in. You can participate regardless of your experience in Data Science - all you need is some curiosity, your computer, and the willingness to talk to other Data Science enthusiasts around you.

------------------------------------------------------------------------------------------

FINAL DETAILS
Please let us know your email address in the mandatory field when RSVPing, so we can include you in the Slack Channel.

What we provide:

• A nice location, refreshments and snacks, WIFI, and a friendly environment so you can connect with your colleagues.

What to bring:

• A laptop, headsets, writing utensils, collaborative mindset, willingness to apply Data Science and your ideas