Course Name: Introduction to data analytics

Course abstract

Data Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us understand our world better, and in many contexts enable us to make better decisions. While this is broad and grand objective, the last 20 years has seen steeply decreasing costs to gather, store, and process data, creating an even stronger motivating for the use of empirical approaches to problem solving. This course seeks to present you with a wide range of data analytic techniques and is structured around the broad contours of the different types of data analytics, namely, descriptive, inferential, predictive, and prescriptive analytics.


Course Instructor

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Dr. Balaraman Ravindran

Prof. Balaraman Ravindran completed his Ph.D. at the Department of Computer Science, University of Massachusetts, Amherst. He worked with Prof. Andrew G. Barto on an algebraic framework for abstraction in Reinforcement Learning. Dr. Ravindrans current research interests spans the broader area of machine learning, ranging from Spatiotemporal Abstractions in Reinforcement Learning to social network analysis and Data/Text Mining
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Dr. Nandan Sudarsanam

Prof. Nandan Sudarsanam holds a Ph.D. in Engineering Systems from Massachusetts Institute of Technology (MIT). His research interests and work experience spans the areas of Data mining/ Machine learning, Experimentation, Applied Statistics, and Algorithmic approaches to problem solving. Dr. Nandan currently works as a faculty member at the Department of Management Studies at IIT-Madras
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Teaching Assistant(s)

PRIYATOSH MISHRA

 Course Duration : Jul-Sep 2016

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 Syllabus

 Enrollment : 23-May-2016 to 18-Jul-2016

 Exam registration : 02-Aug-2016 to 19-Aug-2016

 Exam Date : 18-Sep-2016, 25-Sep-2016