Certified Professional in Business Analytics [UG]

Programme Objectives

The “Certified Professional in Business Analytics [UG]” programme is a comprehensive programme developed for participants interested in carving a career for themselves in the emergent field of business & data analytics. The programme enables participants to position themselves successfully and exploit the rapidly growing demand for Business Analytics specialists in the industry. The programme offers strong conceptual learning, complemented with business case-studies/ use-cases/ examples.
This programme has been designed & developed specifically for under-graduate (UG) participants. A variant of this programme is available for post-graduate (PG) participants, titled the “Certified Professional in Business Analytics [PG]” programme.
The UG programme has a special focus on R programming, and on solving statistical & analytics problems using R. The PG programme has greater focus on business applications of analytics techniques, and has more business case studies/ use cases and projects/ assignments.

Who should go for the Programme?

Dedicated programmes are available for under-graduate (UG) and post-graduate (PG) participants. The under-graduate programme has been designed & developed primarily for graduates in the disciplines of Engineering, Science (Mathematics, Statistics, Physics, Chemistry, etc), Social Science (Economics, etc.), Commerce, and Accountancy. Final-year students in these disciplines (and pre-final year students, in case of Engineering) will also benefit from the programme.
The post-graduate variant of this programme has been designed & developed specifically for post-graduates and graduates in Engineering, Science (Mathematics, Statistics, Physics, Chemistry, etc), Social Science (Economics, etc.), MBA, Commerce, and Accountancy (pursuing CA, ICWA, etc).

Key Takeaways

After successful completion of the “Certified Professional in Business Analytics [UG]” programme, participants will be able to:

Develop awareness of various Statistical, Mathematical & Econometric models used in the industry for business analytics
Participate in/ contribute to business analytics projects in their businesses
Identify the dos-and-don’ts of successful execution & implementation of business analytics projects
Understand how business analytics can help manage business better
Identify the scope of analytics in their business domains

Learning Mode

Curriculum Overview

Introduction to Business Analytics

Descriptive Analytics
Inferential Analytics
Predictive Analytics
Prescriptive Analytics

Introduction to Big Data Analytics

Applications of Big Data Analytics
Map Reduce, Hadoop, etc

Basic Mathematics recapitulation

Linear Algebra
Calculus
Set Theory
Permutations & Combinations

Probability Theory & Probability Distributions

Basic Concepts
Key Applications in Business Analytics
Hands-on implementation using R

Programming in R

Basic Statistics

Different types of data
Different types of measurement scales
Measures of Central Tendency, and applications
Measures of Dispersion, and applications
Measures of Shape Parameters, and applications
Hands-on implementation using R

Correlation Analysis

Statistical Inference

Sampling
Estimation
Testing of Hypothesis
Analysis of Variance (ANOVA)

Linear Regression

Logistic Regression

Segmentation

Hierarchical & non-Hierarchical Segmentation
Cluster Analysis
Hands-on implementation using R

Time Series Analysis

Basics of Time Series Analysis
Forecasting through Exponential Smoothing
Hands-on implementation using R

Operations Research

Supply Chain Management analytics
Need for Optimization in Business Functions
Linear Programming – Concepts & Applications
Hands-on implementation using MS Excel Solver

Introduction to Text Mining

Introduction to Marketing Research

Introduction to Data Mining

Role of Data Mining in Data Analytics
CRISP-DM Methodology

Case studies/ Use cases

Projects/ Assignments

Evaluation/ Examination

Similar Training Programmes

Data Management & Data Mining through R / Python

Business Forecasting

Advanced Data Science / Advanced Machine Learning through Python

Certified Professional in Business Analytics [PG]

Fundamentals of Data Analytics

Are there any Learning Pre-requisites?

There are no specific learning pre-requisites for the programme. Effectiveness of learning through the programme would be enhanced if participants possess good logical & analytical reasoning skills. In order to further enhance the efficiency & effectiveness of participants’ learning, it is desirable that participants have studied, at the graduate or 10+2 level, either of Mathematics, Statistics, Engineering Mathematics, Business Mathematics, or Mathematical Economics.

MEET Our Consultants & Faculty

Dr. Goutam Das

30+ years of industry experience across multiple sectors including Finance, Energy, Telecom, Retail, Media, Manufacturing & Automobiles.

Prof (Dr.) B B Chakraborty

40+ years of experience in Industry and Academics, serving as consultant to major global organizations and Professor at leading IIMs.

Dr. Nidhan Choudhuri

25+ years of global experience in Financial Modeling, Risk Analysis, and Quantitative Trading, with roles at Barclays and Morgan Stanley.

Dr. Ayan Chatterjee

8+ years of R&D experience in AI, Machine Learning, and Medical Image Processing with NVIDIA and AstraZeneca.

Mr. Jayanta Adhikari

30+ years of experience in BFSI and Retail sectors, specializing in Financial Analytics and Digital Transformation.

Ms. Amrita Saha

15 years of experience in AI, GenAI, Big Data Analytics, and Econometrics across BFSI and Energy sectors.

Certified Professional in Business Analytics [UG]
Get well-versed with a wide range of analytics methodologies & techniques prevalent in the industry

6 Months programme

Key Takeaways