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SUMMARY:Data Science for Managers
DTSTART:20190204T083000
DTEND:20190208T190000
DTSTAMP:20260407T051200Z
UID:88d0ee6b5751f4ad5de54308a222c045aa59128ca57692ea45233060
CATEGORIES:Internal trainings
DESCRIPTION:Prof. Kenneth Younge\, Head of the Technology and Innovation S
 trategy Lab\, EPFL Prof. Chris Tucci\, Head of the Corporate Strategy and 
 Innovation Lab\, EPFL Dr. Omid Shahmirzadi\, Post-Doc in Computer Science\
 nWhy take this course?\nThe Harvard Business School calls data science the
  sexiest job of the 21st century\, and McKinsey projects that AI could del
 iver an additional $13 trillion GDP to the global economy by 2030. Current
 ly we see a revolution in data-driven business models\, automation\, and a
 nalysis by the fastest growing companies.\nWhy has data science become so 
 critical to organizations?\nToday\, massive amounts of data are available 
 in all areas of science\, government and industry. Exploited sensibly\, su
 ch raw data can significantly improve the efficiency of research\, service
 s and industries in fields such as healthcare\, engineering\, finance\, te
 lecommunications or urban developments - to name just a few. But before or
 ganizations can build teams\, to then build solutions\, managers need to b
 etter understand the methods\, why they work\, why they sometimes do not w
 ork\, and how to integrate them into their planning. We believe managers w
 ill make better decisions\, and work better with data science teams\, when
  they have first-hand experience working across a range of such methods.\n
   Objectives - Learn the foundational concepts and methods of data scienc
 e\n- Learn how to apply data analysis algorithms to real-world data sets (
 i.e.\, learn some programming)\n- Understand the implications of data-driv
 en business models and strategic planning   Target Audience Professionals
  who want to understand Data Science methods and tools\, so they can bette
 r manage technical experts in the field.   Requirements No prior training
  in Data Science is required\, although participants should be familiar wi
 th:\n- Introductory statistics\n- Basic knowledge of linear algebra\n- Exp
 erience with a computer programming language\n- At least some familiarity 
 with Python is strongly recommended (all demos and exercises in Python)\n-
  The course will be given in English\n- Participants should bring their ow
 n laptop to use during the course
LOCATION:PO 01 https://plan.epfl.ch/?room==PO%2001
STATUS:CONFIRMED
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