Instructor:

Jagannath Aghav

Text Book :

• James R. Evans, “Business Analytics: Methods, Models, and Decisions”, Pearson 2012
• Ethem Alpaydin, “Introduction to Machine Learning,” Third Edition, The MIT Press, 640 pp, August 2014, ISBN: 9780262028189

Reference books:

• Reading Material provided by IIM-R
• John Vezirani, “SimpleR – Using R for Introductory Statistics,” https://cran.r-project.org /doc/contrib/ Verzani-SimpleR.pdf
• Thomas H. Davenport, Jeanne G. Harris and Robert Morison, “Analytics at Work: Smarter Decisions, Better Results”, Harvard Business Press, 2010
• Evan Stubbs, “Delivering Business Analytics: Practical Guidelines for Best Practice”, Wiley 2013
• Management Information Systems by James A O’Rrien, George M Marakas and Ramesh Behl, 9/e, McGraw Hill Publication, 2010
• Decision Support and Business Intelligence Systems by Efraim Turban, Ramesh Sharda and Dursun Delen, 9/e, Pearson Publication, 2011
• Cases from Harvard Business Publication (hbsp.harvard.edu)

Course Outline:

Data analytics (DA) is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.

Course Contents