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MAKING DATA-DRIVING DECISIONS The Data Revolution is in full swing, transforming everything from our daily lives to how we do business. The world has watched in awe as the organizations that are willing, ready, and able to take on the challenge of harnessing the power of data science to make predictions about their customers, the market, and their organization have stood further and further above their peers. But many organizations are struggling to unleash this power for their organizations; progress is stymied by misunderstanding, poor data strategy, and lack of a common language between teams. The directive to make data-driven decisions flounders as teams struggle to understand the fundamental principles of data science. SO, WHAT’S THE SOLUTION? CorpU, in partnership with Foster Provost and Vasant Dhar, are developing a catalyst that will take your team from unsure and misinformed to confident, articulate, and eager to move forward into the opportunities that predictive analytics holds for your organization. Participants will: • Align data and business understanding and develop meaningful solutions to issues such as siloing and mistranslation. • Develop a highly functional familiarity with key data mining concepts, unlocking their ability to communicate with analytics stakeholders. • Demystify the data science process, allowing them to productively engage with industry operations. • Construct a data proposal that will then be crowd-sourced via Idea Tournament to evaluate, hone, and provide to your organization for implementation. • Collaborate to unpack your organization’s current data strategy and propel your organization into new levels of data maturity. Join us in exploring the groundbreaking possibilities of predictive analytics with real-life case studies, a course-long simulation full of twists and turns, collaborative problem solving, and world-class faculty: Module 1 Introduction to Predictive Analytics: what it is, what it isn’t, and the potential value for your organization. Module 2 The Data Mining Process: discover the industry standard data mining technique and unlock it to begin writing a Data Proposal for your organization. Module 3 Introduction to Modeling: demystify the modeling process so that you can engage productively with analytic teams and/or consultants. flexible break (1-3 weeks): conduct data preparation conversations within your organization Module 4 Evaluating and Deploying Your Predictions: learn to evaluate model performance by keeping business understanding at the forefront. Module 5: Leveraging Predictive Analytics for Competitive Advantage: unpack the need for cross-functional data strategies in order to develop sustainable competitive advantage. Module 6: Idea Tournament: each participant submits a cumulative data proposal and estimates the value that realized approach to data could bring to your organization. Proposals are evaluated by the cohort in order to select and further hone 2-4 of the most viable opportunities. About the Faculty FOSTER PROVOST is Professor of Information Systems and Andre Meyer Faculty Fellow at New York University’s Stern School of Business. Professor Provost studies data mining, machine learning, social network analysis and their alignment with business problems. He is also co-author of the guiding text for this course, Data Science for Business. He has won several awards, including the 2009 INFORMS Design Science award for social network-based marketing, IBM Faculty Awards for outstanding research in data mining and machine learning, and a President’s Award from NYNEX Science and Technology. Professor Provost recently retired as Editor-in-Chief of the journal Machine Learning after 6+ years. He is a member of the editorial boards of the Journal of Machine Learning Research(JMLR) and the journal Data Mining and Knowledge Discover. He was elected as a founding board member of the International Machine Learning Society. VASANT DHAR is a professor at NYU’s Stern School of Business and Co-Director of the Center for Business Analytics. In addition to serving as Editor in Chief of the journal Big Data, he has written over 70 research articles, funded by grants from industry and the National Science Foundation. He pioneered the use of machine learning for predictive modeling on Wall Street across proprietary systematic trading, risk management, and customer and sales force management. He is a frequent speaker in academic as well as industrial forums. Guiding Course Text Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Data Science for Business was named by Fortune magazine as one of the top five books for required reading by an MBA student.