Instructor:
Jagannath Aghav
Text Book :
- Management Information Systems: managing the Digital Firm by Ken Laudon, Jane Laudon and Rajanish Dass, 12/e, Pearson Publication, 2013
- 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:
Business analytics (BA) is the practice of iterative, methodical exploration of an organisation's data, with an emphasis on statistical analysis. Business analytics is used by companies committed to data-driven decision-making.
It refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods
Program Outcomes:
The program enables its graduates to:
- Understand the socio-economic, political, technological, and ecological environment of modern societies and their characteristic values;
- Acquire the prevailing state-of-art knowledge and skills in the basic disciplines and functional areas of management;
- Develop analytical and innovative attitudes and skills so as to facilitate change and increase the effectiveness and efficiency of organizational systems; and 4.
- Develop values and proactive attitudes for societal well-being.
Course Learning Outcomes:
Students will be able to:
- Understand the need for IS and its impact to business scenarios,
- Analyze, implement, and adopt with critical business issues associated with information systems,
- Demonstrate the frameworks that could be used while exploring the ways information systems may be leveraged in a business context, and
- Discuss the important key issues for building effective business solution
1. https://cran.r-project.org/
R distributions. The Comprehensive R Archive Network.
2. https://www.rstudio.com/
RStudio for R code editing, visualization, and R packages
3. http://www.kdnuggets.com/2015/06/ top-20-r-machine-learning-packages.html
Machine learning and data science packages of R
4. http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
Visual introduction to the state of the art data science and machine learning
Course Syllabus