Virtual Data Science Camp Fall Edition - Part 1: Tips and tricks or treat ... how to start on the

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When:  Oct 31, 2019 from 09:00 AM to 10:00 AM (PT)

IBM's virtual data science camp in the summer turned out to be quite popular with data  scientists, analysts and developers.  To address some of the common questions as well as new topics, we are bringing back the same presenters from IBM Digital Technical Engagement (DTE).  We will cover  the topics of getting started, collaboration and use cases on October 31, November 7 and November 14 in our live Webinars. We will feature the popular tools eg. AutoAI and SPSS Modeler to automate and augment the data science process.

Part 1: Tips and tricks or  treat ... how to start on the right  foot with data science 

9am Pacific standard time,  Thursday, October 31, 2019

Are you getting into the data science game? Do you want to get your skills up to speed so that you can showcase your knowledge immediately?  Data science seems daunting but if you have the right tools and resources, you can start contributing right away.  Join me to learn how to boost your data science skills. 

By Jacques Roy, Digital Technical Lead, IBM

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Part 2: Bring SPSS and open source skills together

9am Pacific standard time,  Thursday, November 7, 2019

Skill set and constantly having to learn about new tools in data science are still very challenging.  Whether you are a user of SPSS Modeler, Watson Studio or Open Source tools, you can bring your data science projects to production quickly in a unified environment.  Come and learn about collaboration and deployment with IBM Data Science. 

By Matt  Jones, Digital Technical Lead, IBM

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Part 3: Common patterns for predictive and prescriptive analytics

9am Pacific standard time,  Thursday, November 14, 2019

The lines across industry use cases are blurring- many use cases are applicable and proven across multiple industries. You can choose and learn the use cases with high likelihood of success eg. churns, price optimization, workforce planning and demand/supply matching.  Check out this session to learn about the real-world scenarios of putting data science to work for business!

By Nerav Doshi, Digital Technical Lead, IBM

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