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Training Students to Extract Value from Big Data Summary of a Workshop (2015) / Chapter Skim
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6 Workshop Lessons
Pages 40-44

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From page 40...
... WHOM TO TEACH: TYPES OF STUDENTS TO TARGET IN TEACHING BIG DATA Robert Kass opened the discussion session by noting that the workshop had shown that there are many types of potential students and that each type would have different training challenges. One participant suggested that business managers need to understand the potential and realities of big data better to improve the quality of communication.
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From page 41...
... And another proposed examining the Carnegie Mellon University data science master's degrees for common topics taught; those topics probably are the proper subset of what constitutes data science. A workshop participant noted that most institutions do not have nine competing master's programs; instead, most are struggling to develop one.
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From page 42...
... A participant stated that an American Statistical Association committee had been formed to propose a data science program model for a statistical data sci ence program; it would probably include optimization and algorithms, distributed systems, and programming. However, other participants pointed out that that initiative did not include computer science experts in its curriculum development and that that would alter the emphases.
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From page 43...
... Ramakrishnan recommended including algorithms and analysis in computer science. He noted that although grounding instruction in a specific tool (such as R, SAS, or SQL)
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