Prescriptive Analytics (2:0)

Dr M Mathirajan

Department of Management Studies, Faculty of Engineering, IISc

Objective of the course

To provide business practitioners and those who are interested in Prescriptive Analytics with a selected set of Management Science and optimization techniques and discusses the fundamental concepts, methods, and models needed to understand prescriptive-analytics and implement these techniques in the era of Big Data.

Syllabus

Introduction to Business Analytics, Linear/Integer/Non-Linear Optimization, Optimization of Network Models, Dynamic Programming, Heuristic Programming, Goal Programming, Multi-Attribute Decision Making Methods, and Monte Carlo Simulation, which are believed to be among the most popular Prescriptive Analytics tools to solve a majority of business optimization problems, with case studies from Business, Industry, and Government (BIG) applications using LINDO/LINGO/CPLEX optimization package.

Minimum Qualification

ME/MTech, BE/BTech and Masters in Business Administration, Management, Operations Research, Computer Science, Computer Applications, Mathematics, Statistics, Commerce, Economics

Pre-requisites

NIL

Who can apply?

Any personal who are working in any Business, Industry and Government (BIG) organizations as well as academic who needs the basic knowledge of “Prescriptive Analytics” through applications of Prescriptive Analyticsa