# Topic covered
* List Data Structure
* List declaration
* List access
* Mathematical operators for List Objects
* Comparing List objects
* List in-built function
* List Comprehensions

# Topic covered
* String Data Type
* Define String literals
* Slicing of Strings
* String in-built function
* Formatting the Strings

# Topic covered
Python provides the following set of operators
1. Arithmetic Operators
2. Relational Operators or Comparison Operators
3. Logical operators
4. Bitwise operators
5. Assignment operators
6. Identity Operators
7. Membership Operators

# Topic covered
* Flow Control
* Conditional / Decision Making statements
    * if, if-else, if-elif-else
* Iterative Statements
    * for, while
* Transfer Statements
    * break, continue, pass

# Topic covered
* Data Types
* Python inbuilt functions
* Dynamic type and Strong Type
* Python collections

# Topic covered
* Introduction to Python
* Python Name
* Where we can use Python
* Python Versions
* Flavors of Python
* Features of Python
* Why to use Python
* PEP - Python Enhancement Proposal
* Python Library
* Compiled language vs interpreted language
* Identifiers
* Reserved Words (Keywords)
* Process: Making Chai (Tea) - in Pythonic View

Python Roadmap

# Topic covered
Python different version installation in 2 ways
* By - Building Python from Source
* Using deadsnakes PPA (For Latest Python Versions)

Pip installation

# Topic covered
* Virtual Environment introduction
* Need of virtual environment
* Virtual Env types
    * virtualenv
    * virtualenv & virtualenvwrapper

1.1 Data Science

Data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. Data science uses complex machine learning algorithms to build predictive models.

Data Science is a field which incorporates Artificial Intelligence, Data Mining, Big Data, Machine Learning, and Deep Learning.