Predictive Analytics

By Dinesh Kumar | Indian Institute of Management Bangalore (IIMB)

Learners enrolled: 13917

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.

Summary

Course Status :	Completed
Course Type :	Core
Language for course content :	English
Duration :	6 weeks
Category :	Management Studies
Credit Points :	2
Level :	Postgraduate
Start Date :	31 Jul 2023
End Date :	31 Oct 2023
Enrollment Ends :	09 Sep 2023
Exam Date :	30 Nov 2023 IST

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Introduction to Analytics

Week 2: Simple Linear Regression (SLR)
Week 3: Multiple Linear Regression (MLR)
Week 4: Logistic Regression
Week 5: Decision Trees and Unstructured data analysis
Week 6: Forecasting and Time series Analysis

Click here for syllabus

Books and references

None

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

Enrolling and learning from the course is free. However, if you wish to obtain a certificate, you must register and take the proctored exam in person at one of the designated exam centre’s. The registration URL will be announced when the registration form is open. To obtain the certification, you need to fill out the online registration form and pay the exam fee. More details will be provided when the exam registration form is published, including any potential changes. For further information on the exam locations and the conditions associated with filling out the form, please refer to the form.

Grading Policy:

Assessment Type	Weightage
Mid-Term & End-Term	25%
Final Exam	75%

Certificate Eligibility:

40% marks and above in Mid Term & End Term
40% marks and above in the final proctored exam

Score	Type of Certificate
>=90	Gold
75 - 89	Silver
70 - 74	Bronze
40 - 70	Successfully Completed
<40	No Certificate

Sample Certificate:

Disclaimer: In order to be eligible for the certificate, you must register for enrolment and exams using the same email ID. If different email IDs are used, you will not be considered eligible for the certificate.

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