DATA SCIENCE

What is Data Science?
Understand the definition of data science and its various elements

What is difference between Data Analytics and Business Analytics
Understand the subtle difference between Data Analytics and Business Analytics

What are different types of Data Science roles?
5 key data science roles explained- which role do you fit in?

Why data science workflow requires programming?
Learn the benefits of knowing programming to carry out data analysis

What is Data Mining, and how is it used in Business?
Real world cases across different industries, where data mining has benefited businesses.

What is reproducible data science project?
Understand what is reproducible data science workflow and why it is important.

CRISP-DM and KDD methodology - a structured approach to planning a data analytics project.
Learn two widely used data analysis project management methodologies in industry.

R Language

What R is and what it is not?
A brief history of R, its features and limitations

Getting started with R - Part 1: R installation guide
Take the first step in your R journey. Install R program on your machine.

Getting started with R – Part 2: RStudio installation guide
Take the second step in your R journey. Install R development environment on your machine

Unraveling R data types - The Vectors - A gentle introduction
Understand R objects. Create, subset and manipulate vectors - the most basic data type in R

Unraveling R data types - The Matrix - A gentle introduction
Matrices are special class of vectors. Create, Subset and manipulate Matrices

Unraveling R data types - The data-frames - A gentle introduction
Get hands on with data frames - the most widely used data type in R.

Unraveling R data types - The Factors - A gentle introduction
Factors are widely used to manipulate categorical data. Understand Factors and their inner working.

Unraveling R data types - The List - A gentle introduction
Lists are the most flexible data types in R. However they can be difficult to work with.

What are R Packages and how to install them?
R packages are backbone of R language. Understand R package system and installation procedure

Statistics and Probability

What is Statistics and why it is important for data analysis?
In this post you will discover why statistics is important in general and for data science in particular, and types of methods that are available..

A gentle introduction to descriptive statistics – examining univariate distributions
Descriptive statistics is used to describe the data. A first step in this process is to check the distribution of values of each numeric variable. In this tutorial, various tools for describing the variable such as distributions, tabulations and graphical representation are discussed.

How to calculate and visualise the distribution of Numeric Variable?
Learn how to calculate standard deviation, variance and five number summary statistics. The box-plots and violine plots are introduced to check the distribution of numeric variable

A gentle introduction to Covariance and Correlation
Does marketing ad campaign lead to more product revenue? Is there a relationship between thee two variables?

An intuitive real life example of Binomial distribution and how to simulate it in R?
Learn binomial distribution using quality control example

An intuitive real life example of Poisson distribution and how to simulate it in R?
Learn Poisson distribution using customer arrival rate example

An intuitive understanding of Normal Distribution using business example
Learn Normal distribution using sales page loading time example

A gentle introduction to Sampling terms and definitions - A pre-requisite to inferential statistics.
Inferential statistics is based on Sampling theory. Learn some important concepts and definitions from Sampling theory

An intuitive understanding of Sampling distribution and central limit theorem using practical example
Learn what is Sampling distribution and the central limit theorem - one of the most fundamental statistical concept every data scientist should know.

A brief introduction to Linear Transformation
data transformation is used to express a variable in different form. This helps obtain greater insight while expressing a variable in different form. In this blog, you will learn some basic linear transformations and apply them on the data set.

Is your data Normal? A gentle introduction to Normality Test.
There are range of techniques that you can use to check if your data sample deviates from a Gaussian distribution, called normality tests. In this tutorial, we will learn some techniques that can be used to check the normality of the data. 

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