[Bessig] Cementing Data Science as an accredited profession

[Neal McBurnett]

Thanks, Lynn.  Sounds like a great session.  I don't expect I'll be going to AGU, but I have been having a ball with data science recently.

I'm on the team offering two big free online courses (MOOCs):

 Introduction to Big Data with Apache Spark | edX
 https://www.edx.org/course/introduction-big-data-apache-spark-uc-berkeleyx-cs100-1x

 Scalable Machine Learning | edX
  https://www.edx.org/course/scalable-machine-learning-uc-berkeleyx-cs190-1x

The second one has gotten even better reviews than the first, and is still open for enrollment for the next two weeks or so.  If you do all the labs you can still pass it, even with the late penalty, and have access to the material after it ends even if you don't have the free time to finish it now.

I enjoyed this nice reference on what Data Science is, and how the term has been used over the years:

 A Very Short History Of Data Science
  http://www.forbes.com/sites/gilpress/2013/05/28/a-very-short-history-of-data-science/

We have had some great interest in and news about Spark recently, including this:

 IBM Pours Researchers And Resources Into Apache Spark Project
 http://techcrunch.com/2015/06/15/ibm-pours-researchers-and-resources-into-apache-spark-project/#.4xy1fh:9kBI

 "IBM today pledged it would devote 3500 researchers to the open source big data project, Apache Spark. It also announced that it was open sourcing its own IBM SystemML machine learning technology in a move designed to help push it to the forefront of big data and machine learning."

They are teaming up with various partners with the "goal of training one million data scientists in Spark".

You might also be interested in our "Data Detectives of Boulder" group that meets for lunch on Wednesdays to share perspectives and tips on various online courses related to data science:
 https://www.linkedin.com/grp/home?gid=6525462

Cheers,

Neal McBurnett                 http://neal.mcburnett.org/

On Wed, Jul 15, 2015 at 06:42:51PM +0000, Lynn Yarmey via Bessig wrote:
> 
> Hello BESSIG, 
> 
> If you are still contemplating your AGU abstract, please consider presenting at the session I am co-convening with a group of
> fantastic women:  IN049: Towards a Career in Data Science: Pathways and Perspectives.  We would like to see a diverse range of
> perspectives in the discussion, and if there was ever a group that embodied this diversity it would be BESSIG!  It would be great
> to hear your take on the roles (formal and informal) in your part of the data landscape.  
> 
> Feel free to forward along to anyone you think would be interested, and I hope to see you in San Francisco!
> 
> Many thanks, 
> Lynn
> 
> ------------ 
> Lynn Yarmey
> National Snow and Ice Data Center
> University of Colorado Boulder
> 
> 
> Data Science has been described as ‘the hottest job you haven’t heard of.’
> 
> 
> As data became more voluminous, science entered a new mode of operation: that of data intensive science. Slowly and often by
> stealth, a new breed of researcher began to emerge: that of the ‘Data Scientist’ who has expertise in both domain science and
> elements of computer science. They can communicate in both the science and technical fields and are key to translating the data
> deluge into new research insights and awesome results. They are integral to any team generating and processing data, and have an
> essential role in the growing field of interdisciplinary data-driven research.
> 
> 
> But Data Scientists remain largely behind-the-scenes...
> 
> 
> To raise awareness of the potential and rewards of a career in Science Data we are convening this session at the AGU Fall Meeting
> 2015. Please come and tell us about:
> 
>   • YOUR story;
> 
>   • The work YOU do;
> 
>   • The courses YOU are running;
> 
>   • Why YOU are hiring data scientists and the training you need them to have.
> 
> IN049: Towards a Career in Data Science: Pathways and Perspectives
> 
> 
> Session Description:
> 
> Data scientists are playing an increasingly prominent role in earth and space sciences informatics, and large geosciences projects
> in general, yet there are many pathways towards this role. This session will present various perspectives on building a career in
> data science, including: university programs that provide a degree or specialization, with commentary on the career trajectories of
> their graduates; early-career scientists with perspectives on how they successfully landed a data science position; mid-career
> practitioners that have moved from either straight domain science or computer science/IT explaining how they made the transition
> successfully; managers describing the diversity of data science positions they have and how they hire for them; and late-career
> professionals reflecting on their accumulated experience and the trends that they see.
> 
> 
> Our confirmed Invited Presenters are :
> 
> 
> Cyndy Chandler: Information System Specialist, Woods Hole Oceanographic Institution
> 
> 
> Kerstin Lehnert: Senior Research Scientist, Lamont-Doherty Earth Observatory, Columbia University
> 
> 
> Carole Palmer: Professor, Information School, University of Washington
> 
> 
> Read more on: https://agu.confex.com/agu/fm15/preliminaryview.cgi/Session8942
> 
> 
> Here is a direct link to submit: https://agu.confex.com/agu/fm15/in/papers/index.cgi?sessionid=8555
> 
> 
> Please note that abstracts are due by Wednesday, August 5, 2015 at http://fallmeeting.agu.org/2015/abstract-submissions
> 
> 
> BUT if you submit before the 29 of July you could be eligible for a free registration:  http://fallmeeting.agu.org/2015/
> submit-early-win-big-rules-and-guidelines/
> 
> 
> 
> Karen Stocks, Ruth Duerr, Lynn Yarmey and Lesley Wyborn