Affiliate Post Business and Management

Course on Predictive Analytics by Indian Institute of Management, Bangalore [7 Weeks]: Enroll Now!

Start your future on Coursera today.
By: Rashmi | 11 Feb 2020 4:30 PM

About the Course

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.

Instructor

Dinesh Kumar Professor, Decision Sciences & Information Systems Indian Institute of Management, Bangalore

To enroll for this course, click the link below.

Course on Predictive Analytics

Note: Noticebard is associated with edX through an affiliate programme.

Get Noticebard’s Posts in Your Email.

Jobs, internships, conferences, scholarships, etc.
Join 38,000 other people!

Related Posts

About the Author

Rashmi

Comment via Facebook

Comment via Website

Your email address will not be published. Required fields are marked *