on Business Analytics, Data Mining and Operations Research
Indian Statistical Institute Delhi Centre
Results for Certification
Program on Business Analytics, Data Mining and Operations Research Examination
Business analytics is a discipline that
focuses on understanding business performance and developing new
strategies based on data and statistics. It uses specialized techniques
and tools to gather information, organize data and interpret it to
support business decision making. Business intelligence professionals
make use of programming software like SPSS, Minitab, Matlab
& R and management skills to improve efficiency, financial
performance and implement strategic solutions.
The program offers rigorous, hands-on training that will prepare you to
use data and analytics to identify business opportunities, generate
business insights and create business solutions.
fee: Rs. 50,000/- + (GST 18%)=Total Rs 59000/- per participant which include course
material, lunch and refreshment.
Profile: Bachelor's degree with Mathematics/Statistics/
Physics or BE/B Tech degree or MBA, or Six Sigma black belt
16-19, 2019, October 21-24, 2019, November 19-22, 2019, December 9- 12,
2019 (16 days).
December 13, 2019 (Friday)
Coordinator: Professor S. K. Neogy (ph. No. 011-41493966, e.mail:firstname.lastname@example.org,
For Certification Program on Business Analytics,
Data Mining and Operations Research please send your participant details
along with bio-data and Registration
form (download the form as pdf file) on or before
August 26, 2019 to the Progammme Coordinator in the mailing address given below.
Please ensure that you satisfy the eligibility
criteria. If you do not satisfy eligibility criteria/ qualification
criteria, then your application will be rejected and draft will be sent
back to your address. For further details, visit http://www.isid.ac.in/~sqc/badmor.html
or write to programme coordinator, Professor S.
K. Neogy (e.mail: email@example.com).
Mailing address: Professor S. K. Neogy
no. 320/ 318 Faculty Block
& OR unit, Indian Statistical Institute,
S. J. S. Sansanwal Marg,
Delhi: 110016, India
No: 41493968, 41493966
e.mail: firstname.lastname@example.org, email@example.com
Module 1: Introduction, Basic Concepts and Visual
Analytics using R
-Introduction to Analytics and concepts of
statistical / machine learning / analytics problems, Developing a
Predictive Business Analytics Function
-Introduction to random experiments and random
variable, concepts of parameters, concepts of visual analytics using
random variables and their parameters, different summary measures and
presentations, examples and exercises
-Graphs and Charts for data visualization
-Sampling Concept and Methods
Module 2: Probability distributions, Estimation and
-Distribution as a model of a business process;
usage of distribution for decision making.
-Probability and Distributions, understanding
normal distribution, brief introduction to some useful distributions,
-Estimation and hypothesis Testing
-Estimation of parameters like means, variances,
proportions and model parameters in different circumstances and their
usages in analytics;
-Concepts of standard errors and confidence
-Theory of estimates; concept of likelihood,
sufficiency and information criteria.
-Formulating hypotheses in real life scenarios
-Test for means, variances, proportions, odds
ratios and relative risks
Module 3: Prediction Modeling through Regression
-Simple and multiple linear regressions.
-Concepts of cross validation, usage of validation
set, k fold cross validation and concepts of bootstrap.
-Multivariate data analysis
Module 4a: Tree based Method, Forecasting and
-Classification and Regression Tree including
concepts of bagging, random forests and boosting, fitting and validating
tree based models
-Forecasting by using AR, MA and ARMA models.
Moving average and Exponential smoothing for forecasting, Measure of
-Cluster analysis, carrying out non-hierarchical
clustering, choosing the right solution for non-hierarchical clustering
Module 4b: Operations Research, Neural Network and
Text as Data: Text Mining and Sentiment Analysis, Market Basket Analysis: Association Rules and
-Introduction to deep learning including project
-Wrap up and examination
After each module assignments will be given.
Participants need to carry out the assignments in team and present the
finding in first day of next module.