COURSE OBJECTIVE

Analytics is emerging as a competitive strategy across many sectors of business. Extant literature claims that analytics is one of the primary differentiators between high performing and low performing companies. Analytics is classified into three major categories: 1. Descriptive Analytics, 2. Predictive Analytics and 3. Prescriptive Analytics.

 Predictive analytics is an area of data mining that deals with extracting information from data and using it to predict trends and behavior patterns. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

Who Should attend :The workshop 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. 

Pre requisites :The participant has to learn at least one of the following statistical software:SAS, SPSS, STATA and R.  This will enable to solve real-life analytics problems.

Predictive analytics searches for patterns found in historical and transactional data to understand factors associated with business/organizational problems.  At an abstract level, predictive analytics can be seen as a set of tools with capability to predict future events. In many business problems, predicting a future event will be useful for effective management.  Models such as multiple linear regression, logistic regression, 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 the relationships can be exploited to make decisions. The primary objective of this course is to understand how predictive analytics tools can be used to analyse real-life business problems such as prediction, classification and discrete choice problems. The focus will be on case-based practical problem-solving using predictive analytics techniques to interpret model outputs. Participants will be exposed to software tools such as MS Excel, R, SPSS, and SAS; and taught how to use these software tools to perform regression, logistic regression and forecasting.

UNICOM trainer is a Professor of Quantitative Methods at IIM Bangalore and holds a Ph.D. in Mathematics from IIT Bombay.  Dr Dinesh Kumar introduced Business Analytics elective course in 2008 to the PGP students at IIM Bangalore and started one of the first certificate programmes in Business Analytics in India in 2010.

He has over 20 years of teaching and research experience.  Prior to joining IIM Bangalore, Dr Dinesh Kumar has worked at several reputed Institutes across the world including Stevens Institute of Technology, USA; University of Exeter, UK; University of Toronto, Canada; Federal Institute of Technology, Zurich, Switzerland; Queensland University of Technology, Australia; Australian National University, Australia and the Indian Institute of Management Calcutta.

Eleven of his case studies on Business Analytics based on Indian organizations such as Aavin Milk Dairy, Apollo Hospitals, Hindustan Aeronautics Limited, Indian Premier League, Shubham have been published at the Harvard Business Publishing.

How much Hands-on is involved?We will be setting up Hadoop, doing hands on on HDFS, and then running a Map Reduce job on Hadoop. We will also be doing a hands on exercise on Hive.

How can I make payment?

Payment can be made via Cheque / DD / Online Funds transfer / Cash Payment.

Cheque should be drawn in favour of "Unicom training and Seminars Pvt Ltd" payable at Bangalore

NEFT Payment:Account Name: UNICOM Training & Seminars Pvt LtdBank Name : State Bank of IndiaBank Address: Ground Floor, K V Plaza, Green Glen Layout, Outer Ring Road, Bangalore.A/c Number : 31729010535IFSC : SBIN0012706A/c Type: Current

What is Course timing?0900 – 1700

Whom do I contact for more details?+91-9538878795 or contact@unicomlearning.com