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

6 Months programme

Contact hours: 200 hours

  • Conceptual Learning
  • Hands-on Learning
  • Projects/ Assignments
  • Case studies/ Use cases
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

  • 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

Descriptive Analytics
Inferential Analytics
Predictive Analytics
Prescriptive Analytics
Applications of Big Data Analytics
Map Reduce, Hadoop, etc
Linear Algebra
Set Theory
Permutations & Combinations
Basic Concepts
Key Applications in Business Analytics
Hands-on implementation using R
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
Testing of Hypothesis
Analysis of Variance (ANOVA)
Hierarchical & non-Hierarchical Segmentation
Cluster Analysis
Hands-on implementation using R
Basics of Time Series Analysis
Forecasting through Exponential Smoothing
Hands-on implementation using R
Supply Chain Management analytics
Need for Optimization in Business Functions
Linear Programming – Concepts & Applications
Hands-on implementation using MS Excel Solver
Role of Data Mining in Data Analytics
CRISP-DM Methodology

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

Goutam Das

M. Tech. (Computer Engineering), IIT Kharagpur

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Dr Nidhan "Neal" Choudhuri

Ph.D. (Statistics), Michigan State University

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Dr Chiranjit Acharya

B.E., M.E., & Ph.D. (Computer Science), Jadavpur University

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Sangeet Pal

PGDM (MBA), IIM Ahmedabad

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Pravin Bhosale

B.E. (Mechanical Engineering), Shivaji University, Maharashtra

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Anirban Bhaduri

B.E. (Computer Science), IIEST Calcutta (e.k.a. Bengal Engineering & Science University)

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Shyam Karmakar

Chartered Statistician at The Royal Statistical Society, London

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Shamik Choudhury

M. Tech. (Computer Science), Indian Statistical Institute, Calcutta

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