Fundamentals of Data Analytics
Structured learning environment for participants interested in carving out a career for themselves in the emergent field of business & data analytics.

72 Hours programme

Contact hours: 48 hours
  • Conceptual Learning
  • Hands-on Learning
  • Projects/ Assignments
  • Case studies/ Use cases
For Enrollment
Programme Objectives
The “Essentials of Business Analytics” programme offers a structured learning environment to participants interested in carving out a career for themselves in the emergent field of business & data analytics. The programme also serves to plug in the learning pre-requisites for advanced/ specialized insAnalytics training programmes, such as (i) Data Mining, (ii) Business Forecasting, and (iii) Artificial Intelligence & Machine Learning.
Who should go for the Programme?
The “Essentials of Business Analytics” programme offers substantial value to all participants who wish to enter the rapidly-growing analytics industry.

Key Takeaways

  • Articulate the fundamental concepts of Mathematics/ Statistics that form the core building blocks of most Analytics learning programmes
  • Appreciate the role played by Mathematics/ Statistics in the design, structure and operations of most frameworks & algorithms applied in Analytics
  • Fulfil the learning pre-requisites for advanced/ specialized insAnalytics training programmes
  • Effectively leverage their learnings in all insAnalytics training programmes
  • Conveniently reuse their learnings across Analytics training programmes across the globe

Learning Mode

Curriculum Overview

What is Business Analytics?
Business Intelligence versus Business Analytics
Descriptive Analytics
Predictive Analytics
Prescriptive Analytics
[Implementation through Excel, R and Python]
Central Tendency & Dispersion
Measures of Shape Parameters
[Implementation through Excel, R and Python]
Sampling & Estimation
Testing of Hypotheses
Analysis of Variance (ANOVA)
[Implementation through Excel, R and Python]
Correlation Analysis
Linear Regression
[Implementation through R and Python]

Are there any Learning Pre-requisites?

Participants must have studied, at the 10+2 level (or later), either of Mathematics, Statistics, Engineering Mathematics, Business Mathematics, or Mathematical Economics.

Enrollment

Fundamentals of Data Analytics

MEET Our Consultants & Faculty

Dr. Goutam Das

Ph.D. (Economics) IIFT Delhi, M. Tech (Computer Engg) IIT Kharagpur
B.E. (Electronics & Comm) V-NIT Nagpur
30+ Years of experience in IT and Analytics [Business Analytics, Big Data Analytics, AI Machine Learning.
Ex-Cheif Data Scientist at Power Foundation of India...

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Dr. Nidhan "Neal" Choudhuri

Ph.D. (Statistics), Michigan State University.
B. Stats. & M. Stats., Indian Statistical Institute, Calcutta.
Ex-Chief Scientist & Founder, PlanetRisk Inc, Bethesda, US.
20+ years of industry exp. with Morgan Stanley, Barclays Capital etc.

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Mr. Aditya Biswas

B. Tech. (Mechanical) & M. Tech (Industrial Engg. & OR) IIT, Kharagpur.
Ex-Principal Consultant in TCS, Head of IT in Allahabad Bank.
Specialized in Process Optimization, R & D and Management Consulting.
30+ yrs of industry exp.

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Gautam Mukherjee

B.Tech (Electronics & Comm) IIT Kharagpur, M.Tech (Electrical Engg) IIT Madras.
30+ Years of experience in R&D in IT, Telecom. Ex Scientist at DRDO

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Somnath Sinha

B.Tech. (Electrical Engg), IIT Bombay.
PGDM, IIM Calcutta.
20+ yrs with IBM as IT Services Leader, CIO, HR Director &s Director, Integrated Operations.
Partnered with Accenture, IBM, PwC, KPMG, E&Y, etc.
30+ years of industry exp.

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Prof. B. B. Chakrabarti

Ph.D. in Economics, Gold Medalist PGDM, IIM Calcutta.
Gold Medalist - BE, Jadavpur Univ.
20+ yrs as a Renowned Prof of Finance at IIM Calcutta.
24+ years of Industry experience with United Nations, Deustche Bank etc.

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