Prescriptive Analytics

Dr M Mathirajan

Chief Research Scientist

Department of Management Studies, Faculty of Engineering

Objective

To provide, business practitioners and those who are interested in Prescriptive Analytics, a selected set of Management Science and Optimization Techniques along with the fundamental concepts, methods, and models for understanding prescriptive-analytics and implementation of these techniques in the era of Big Data.

Syllabus

“Introduction to Prescriptive 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. These 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/etc. optimization package.

Target Audience

“Every Business, Industry and Government (BIG) organizations which has “Business Analytics” group to address various problems associated with Prescriptive Analytics. In addition, all Faculty and interested UG and PG Graduates in Engineering and Post Graduate in Business Administration/Management, Operations Research, Computer Science, Computer Applications, Mathematics, Statistics, Economics.