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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.


Fundamentals of Data Analytics

MEET Our Consultants & Faculty

Goutam Das

Ph.D. Scholar (Foreign Direct Investment), IIFT Delhi MTech (Computer Engg.), IIT Kharagpur Alumnus of IIM Calcutta & ISI Delhi 25+ yrs of industry exp. across industry verticals

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Dr Nidhan "Neal" Choudhuri

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

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Debjani Bhattacharya

M. Phil, Jadavpur University, B.E. (Electrical Engg.), MN-NIT Allahabad

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Dr. Mousumi Duttaray

Ph.D. (International Economics), Indiana University, USA 18+ years of teaching, research and industry experience in USA with global majors like Barclaycard, AMEX etc.

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Amrita Saha

M.Sc.(Economics) Calcutta University

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Somnath Sinha

B.Tech. (Electrical), IIT Bombay PGDM, IIM Calcutta 30+ yrs. of exp. in global delivery with 2 decades of service with IBM as Service Leader (IT) & CIO Ex-partner of Accenture, KPMG, E&Y, PWC

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Prof. B. B. Chakrabarti

Ph.D. in Economics Gold Medalist -PGDM, IIM Calcutta Gold Medalist - BE, Jadavpur Univ. Fellow Member of the Institute of Cost Accountants of India (ICAI) 40+ yrs of experience in industry/ academic

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Pravin Bhosale

B. E. (Mech. Engg), NIIT PG Certification on Business Analytics, Machine Learning Cert from Stanford Univ. LOMA ALMI Certified Professional 15+ years of experience in consulting on Financial Analytics, Credit Risk Analytics, Operations Research, Business Analytics,

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