Fundamentals of Data Analytics

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

After successful completion of the “Essentials of Business Analytics” programme, participants will be able to:

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

Introduction to Business Analytics

What is Business Analytics?
Business Intelligence versus Business Analytics

Different Types of Business Analytics

Descriptive Analytics
Predictive Analytics
Prescriptive Analytics

Probability Distributions

R Programming Fundamentals

Python Programming Fundamentals

Descriptive Analytics

[Implementation through Excel, R and Python]
Central Tendency & Dispersion
Measures of Shape Parameters

Inferential Analytics

[Implementation through Excel, R and Python]
Sampling & Estimation
Testing of Hypotheses
Analysis of Variance (ANOVA)

Correlation & Regression

[Implementation through Excel, R and Python]
Correlation Analysis
Linear Regression

Case studies/ Use cases

[Implementation through R and Python]

Projects/ Assignments

Evaluation/ Examination

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Certified Professional in Business Analytics [PG]

Comprehensive R Programming

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Advanced R Programming

Advanced SAS Programming

Base SAS Programming

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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.