{"id":264432,"date":"2016-07-13T13:57:08","date_gmt":"2016-07-13T20:57:08","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=264432"},"modified":"2017-09-26T08:02:02","modified_gmt":"2017-09-26T15:02:02","slug":"faculty-summit-2016-meeting-the-challenge-of-educating-data-scientists","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/faculty-summit-2016-meeting-the-challenge-of-educating-data-scientists\/","title":{"rendered":"Faculty Summit 2016 – Meeting the Challenge of Educating Data Scientists"},"content":{"rendered":"

With the advancement of data production, storage capabilities, communications technologies, computational power, and supporting computational infrastructure, data science is now recognized as a highly-critical growth area with impact across many sectors including science, government, finance, health care, manufacturing, advertising, retail, and others. As such, this has created a supply problem for highly trained data scientists. And since data science technologies are being leveraged to drive crucial decision making, it is of paramount importance to be able to educate professionals with an appropriate skill set to use appropriate rigor when they draw inferences from data. This means they need a broad set of skills that cut across multiple disciplines from statistics to computer science as well as strong critical reasoning in the context of specific business and scientific needs.<\/p>\n

People<\/h3>\n

Moderator:<\/strong> Kristin Tolle (opens in new tab)<\/span><\/a>, Microsoft
\nPanelists:<\/strong><\/p>\n