Predictive Analytics

By Dinesh Kumar   |   Indian Institute of Management Bangalore (IIMB)
Learners enrolled: 2113
Decision makers often struggle with questions such as: What should be the right price for a product? Which customer is likely to default in his/her loan repayment? Which products should be recommended to an existing customer? Finding right answers to these questions can be challenging yet rewarding.

Predictive analytics is emerging as a competitive strategy across many business sectors and can set apart high performing companies. It aims to predict the probability of the occurrence of a future event such as customer churn, loan defaults, and stock market fluctuations – leading to effective business management.

Models such as multiple linear regression, logistic regression, auto-regressive integrated moving average (ARIMA), decision trees, and neural networks are frequently used in solving predictive analytics problems. Regression models help us understand the relationships among these variables and how their relationships can be exploited to make decisions.

This course is suitable for students/practitioners interested in improving their knowledge in the field of predictive analytics. The course will also prepare the learner for a career in the field of data analytics. If you are in the quest for the right competitive strategy to make companies successful, then join us to master the tools of predictive analytics.

What you'll learn
  • Understand how to use predictive analytics tools to analyze real-life business problems.
  • Demonstrate case-based practical problems using predictive analytics techniques to interpret model outputs.
  • Learn regression, logistic regression, and forecasting using software tools such as MS Excel, SPSS, and SAS.
Course Status : Completed
Course Type : Core
Duration : 6 weeks
Start Date : 31 Jan 2021
End Date : 30 Apr 2021
Exam Date :
Enrollment Ends : 28 Feb 2021
Category :
  • Management Studies
Credit Points : 2
Level : Postgraduate

Page Visits

Course layout

Week 0: Course Prerequisites
  • Course Overview
  • Descriptive Analytics
  • Probability Distribution
  • Hypothesis Testing
  • Analysis of Variance
  • Software Installation
Week 1: Introduction to Analytics 
  • Introduction to Analytics
  • Analytics in Decision Making
  • Game changers & Innovators
  • Predictive Analytics
  • Experts view on Analytics
Week 2: Simple Linear Regression (SLR)
  • Case-let Overview
  • Introduction to Regression
  • Model Development
  • Model Validation
  • Demo using Excel & SPSS
Week 3: Multiple Linear Regression (MLR)
  • Multiple Linear Regression
  • Estimation of Regression Parameters
  • Model Diagnostics
  • Dummy, Derived & Interaction Variables
  • Multi-collinearity
  • Model Deployment
  • Demo using SPSS
Week 4: Logistic Regression
  • Discrete choice models
  • Logistic Regression
  • MLE Estimation of Parameters
  • Logistic Model Interpretation
  • Logistic Model Diagnostics
  • Logistic Model Deployment
  • Demo using SPSS
Week 5: Decision Trees and Unstructured data analysis
  • Introduction to Decision Trees
  • CHI-Square Automatic Interaction Detectors (CHAID)
  • Classification and Regression Tree (CART)
  • Analysis of Unstructured data
  • Naive Bayes algorithm
  • Demo using SPSS
Week 6: Forecasting and Time series Analysis
  • Forecasting
  • Time Series Analysis
  • Additive & Multiplicative models
  • Exponential smoothing techniques
  • Forecasting Accuracy
  • Auto-regressive and Moving average models
  • Demo using SPSS

Instructor bio

Dinesh Kumar

Indian Institute of Management Bangalore (IIMB)
Professor Dinesh Kumar is a professor of Quantitative Methods and Information Systems at the Indian Institute of Management Bangalore. Recognized as one of the Top 10 Most Prominent Analytic Academicians in India, Professor Dinesh is the course director of Business Analytics and Intelligence Executive Education Programme conducted by IIM Bangalore. His main research and teaching interest are Business Analytics and Systems Engineering. He has published a number of case studies at the Harvard Business Publishing on the use of predictive and prescriptive analytics by the Indian companies, and authored more than 70 research articles and 2 books.

Course certificate


Type of exam: 
Computer based exam 

You will have to appear at the allotted exam centre and produce your Hall ticket and Government Photo Identification Card for verification and take the exam in person. You can find the final allotted exam centre details in the hall ticket. The questions will be on the computer and the answers will have to be entered on the computer; type of questions may include multiple choice questions, fill in the blanks etc.


Weightage: 25% weightage for weekly assignment + 75% weightage for final exam. 

Passing Marks: You will be eligible for Certificate only if you score minimum 40% in Weekly Assessment and minimum 40% in Final Exam. 

If you score less than 40% in either weekly assessments (average) or in final exam, you will not receive the certificate. 

MHRD logo Swayam logo


Goto google play store