This document provides an introduction to data science, including what it is, its components and uses. It discusses the life cycle and tasks of a data scientist. It also covers Python as a programming language for data science, how to install Anaconda and Jupyter Notebook, basic Python concepts like data types, functions and statements. Key tools like Anaconda and Jupyter Notebook are introduced for working with Python for data analysis and visualization.
2. Why Data Science ?
❖ The term “Data Science” was created in the early 1960s.
❖ Data science is a future-proof industry.
❖ Continue to grow along with artificial intelligence, computer science, and deep
learning technologies.
❖ Data Science enables companies to efficiently understand gigantic data from
multiple sources.
3. What is Data Science?
❑ Data Science is a new powerful approach to make
discoveries from the data.
❑ An automated way to analyze enormous amount of
data and extract information from it.
❑ A new discipline that combines aspects of statistics,
mathematics, programming and visualization.
9. What is Python?
❑ Python is a simple, general purpose, high level, interpreted scripting language and
object-oriented programming language .
❑ It was created by Guido van Rossum, and released in 1991.
❖ Easy to use and Learn
❖ Expressive Language
❖ Interpreted Language
❖ Object-Oriented Language
❖ Open Source Language
❖ Extensible
❖ Learn Standard Library
❖ GUI Programming Support
❖ Integrated
❖ Embeddable
❖ Dynamic Memory Allocation
❖ Wide Range of Libraries and Frameworks
Features of using Python
10. Anaconda Distribution
Anaconda is a distribution of the Python and R programming languages for scientific
computing (data science, machine learning applications, large-scale data processing, predictive
analytics, etc.)
Installing of Anaconda Python distribution:-
Python can be downloaded through Anaconda distribution platform because it has large
number of inbuilt python packages
By clicking on this link we can download anaconda python distribution.
https://www.anaconda.com/products/distribution
12. An IDE (Integrated Development
Environment) understand your
code much better than a text
editor. It usually provides features
such as build automation, code
linting, testing and debugging.
Jupyter Notebook:-
The Jupyter Notebook is an open
source web application that you can
use to create and share documents
that contain live code, equations,
visualizations, and text.
IDEs for Python