Python Introduction | Python Programming For Beginners | Python Tutorial | Tanmay Panchal

Python Introduction

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Python is defined a
• General purpose
• Interpreted,
• Interactive,
• Object-oriented, and
• A high-level programming language

By general purpose, it means that it can be used for a variety of projects. For example, it’s used in web applications as a data mining language and as a language that handles multiple text manipulations or shell scripting programs.

Python can be used to develop different kinds of applications very easily. It’s an interpreter language that comes with an interpreter shell. You can write a single line of code and run it. You can build your logic by running code line by line and executing it. This is the reason Python being very handy. For interactive developed, Python followed object-oriented programming or OOPs concepts.

You can create classes. You can also create objects of classes and these classes have variables and functions. It’s very similar to any other OOPs language like Java or C sharp. It’s a high-level programming language that makes it easy for the developer to write any business logic without bothering about memory management and other things. You can develop your solutions with very few lines of code.

Python is an open-source language. It’s distributed under General Public License which is also called GPL. You can download Python from the link highlighted on the screen. You can also get Python documents and different releases related information from this website.

Introduction to Python Tutorial
What is Python
Why is Python Popular
Features of Python
Where is Python used in the Industry
Python Learning Path
Python Career Opportunities

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors, and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques, and Regular expressions using modules in Python
5. Gain expertise in machine learning using Python and build a Real-Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming features in Hadoop, and MapReduce job running with Python
10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop, and/Or MRjob Basics
11. Master the concepts of Web scraping in Python
12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands-on Project Experience

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Why learn Python?

Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple-to-read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built-in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, and Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for commercial products, because of its OSI-approved open-source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicate that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.

Who should go for python?

Python is a good fit for the below professionals:

· Programmers, Developers, Technical Leads, Architects
· Developers aspiring to be a ‘Machine Learning Engineer'
· Analytics Managers who are leading a team of analysts
· Business Analysts who want to understand Machine Learning (ML) Techniques
· Information Architects who want to gain expertise in Predictive Analytics
· 'Python' professionals who want to design automatic predictive models

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