Data science is the process of deriving knowledge and insights from a huge and diverse set of data through organizing, processing and analysing the data.

It involves many different disciplines like mathematical and statistical modelling, extracting data from it source and applying data visualization techniques. Often it also involves handling big data technologies to gather both structured and unstructured data. Below we will see some example scenarios where Data science is used.

Chapters Included

Data Science Introduction
Data Science Environment Setup
Pandas
Numpy
Matplotlib

Data Operations
Data cleansing
Processing CSV Data
Processing JSON Data
Processing XLS Data
Relational databases
NoSQL Databases
Date and Time
Data Wrangling
Data Aggregation
Reading HTML Pages
Processing Unstructured Data
word tokenization
Stemming and Lemmatization

Chart Properties
Chart Styling
Box Plots
Heat Maps
Scatter Plots
Bubble Charts
3D Charts
Time Series
Geographical Data
Graph Data

Measuring Central Tendency
Measuring Variance
Normal Distribution
Binomial Distribution
Poisson Distribution
Bernoulli Distribution
P-Value
Correlation
Chi-square Test
Linear Regression