Join us at AnacondaCON!

Apr 4, 2018 · New York, United States of America

Anaconda is hosting its second annual conference in Austin in a month.

A Data Science Conference in Austin in April?!? Can't think of many other places and times better to spend a week 'working'. It promises to be an engaging, informative, and very fun event. Anaconda have offered our group a 30% off discount using the code ACON-BEOURGUEST.

Check out the conference web site: https://anacondacon.io/

What they've asked us to share:

• AnacondaCON 2018 will feature:

- 3 Conference Tracks: Real World Data Science, Open Source Technology, and Anaconda Enterprise

- Over 45 talks covering the latest trends and best practices in data science, machine learning, and AI

- A full day of tutorials on machine learning techniques, Anaconda for enterprises, and package management with conda

- Networking opportunities with a passionate community of data scientists, IT professionals, analysts, developers, and business leaders

• What you need to know

- Conference website: https://anacondacon.io/

- AnacondaCON 2018 is being held at the JW Marriott in downtown Austin on April 8-11.

- We’re offering a bonus 10% off ticket price if attendees book a hotel room at the JW Marriott, where Anaconda has rooms reserved at a special rate.

- Tutorials are being held on Sunday, April 8, and the conference is April 9-11. Please note that tutorial registration is separate from conference registration.

- Finally, there's also a customizable Justification Letter for attendees to show their employers.

Event organizers
  • PyData NYC

    PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to)

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