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Data Science Education Meeting

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This community site will accumulate resources relevant to developing and implementing programs in data science.  It is an outcome of an NSF-funded workshop, held October 1 - 3, 2015 in Crystal City (Arlington, VA).  The meeting was chaired by Boots Cassel (cassel@acm.org) and Heikki Topi (htopi@bentley.edu) and both are happy to address questions.  

We are now in the process of developing the report of the workshop results.  The workshop brought together a very diverse set of people who approach data science from a number of different perspectives.  The report will attempt to capture the areas of consensus and give due attention to the areas where there are differences of opinion.  The report generation will be an open, collaborative process, with input welcome from all who attended.  Comments from those interested in the topic, but who were not at the meeting, may also be valuable.  


jeffp's picture

The outline looks good.  No major comments.  

I mainly wanted to point out an interesting paper from MSR I recently came across.  The paper details the result of interviewing a bunch of data scientists working with software teams inside Microsoft to try to figure out what they actually did day-to-day and what skills they were actually using.  


Its probably biased towards a certain class of data scientists (ones working in CS teams in industry -- not in say univesity science labs) .  But still, I would guess, the experiences are fairly broadly relevant.  

By jeffp
bootsprojects's picture

Getting a good collection of resources is a valuable part of this activity.  Thank you for this one, and for the approval of the outline.



By bootsprojects

I attended the Data Science Education BOF at SIGCSE and have found myself here. I'm interested in helping to support Data Science Education from a combo industry/academic perspective, especially in machine and deep learning.

NVIDIA has recently partnered with Professor Yann LeCun of New York University (NYU) to develop a machine learning Teaching Kit covering the academic theory and application of machine and deep learning on GPUs. The curriculum addresses a wide range of critical machine learning topics enabling educators to empower their students with the AI skillsets they’ll need in industry. Other Teaching Kits offered cover Accelerated Computing and Robotics. Instructors can get access to the Teaching Kits at developer.nvidia.com/teaching-kits.

I would also like to invite everyone to GTC17. You can save USD$1200 off the regular registration rate using my personal code NVJBUNGO on top of the non-profit registration + training. The conference is May 8-11 in San Jose, CA. Among many other things, there will be more than 30 hands-on instructor-led labs across machine learning and GPU programming.

Thanks for taking a look. Feel free to reach out to me directly at jbungo@nvidia.com.

Kind Regards,

GPU Educators Program Manager
NVIDIA Corporation | Academic Programs

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By jbungo
bootsprojects's picture

Envisioning the Data Science Discipline


It is possible to register and "sit in" on these via the Web.

By bootsprojects