Complete Python Roadmap

I am sharing Python lessons from scratch to intermediate with practice sets which I have studied into my Journey of Data Science.

For more detials, refer: Data Analyst Roadmap :hourglass:

Overview of Python Programming

Python is an object-oriented programming language that was created with an emphasis on readability and simplicity. It has been used as the language of choice for Machine Learning, Artificial Intelligence, Web Application Development, and more recently Data Science - Python's strength is its versatility.

Since it’s relatively easy to learn, Python has been adopted by many non-programmers such as accountants and scientists, for a variety of everyday tasks.

What can you do with Python? Some things include:

• Data analysis and machine learning

• Web development

• Automation or scripting

• Software testing and prototyping

• Many more Everyday tasks

Certifications 📜 🎓 ✔️

• Data Analysis with Python - by IBM

• Data Visualization with Python - by IBM

• Pandas - by Kaggle

• Numpy - by Great Learning

• Matplotlib - by Great Learning

• Databases and SQL for Data Science with Python - by IBM

• Statistics for Data Science with Python - by IBM

Featured projects:question: 👨‍💻 🛰️

Data Analyst Roadmap :hourglass:

Library Management System using Python on Django 👨‍💻

Spotify Data Analysis using Python 📊

Sales Insights - Data Analysis using Tableau & SQL 📊

Statistics for Data Science using Python 📊

Kaggle - Pandas Solved Exercises 📊

Python Libraries for Data Science Roadmap 🗂️

Python Lessons for Data Science

Python has become a staple in data science, allowing data analysts and other professionals to use the language to conduct complex statistical calculations, create data visualizations, build machine learning algorithms, manipulate and analyze data, and complete other data-related tasks.

Python can build a wide range of different data visualizations, like line and bar graphs, pie charts, histograms, and 3D plots. Python also has a number of libraries that enable coders to write programs for data analysis and machine learning more quickly and efficiently.

Sr.No. 🔢	Lessons 📕	Reference Links :link:	Exercises 👨‍💻
1	Python Basics - Features Applications, Python 2 vs Python 3, Libraries uses, Interpreter Prompt, Script mode programming, IDEs, Features of an IDE, Compiler vs Interpreter, Pycharm - Featues, Important tools, Useful Plugins	JavaTpoint	Exercise 1
2	Modules, Comments, Pip, Docstrings	Geeks for Geeks	Exercise 2
3	Indentation, Packages in Python, Modules vs Packages	YouTube 1
4	Variables, Declaring & Assigning Values, Object references, Object identity, Variable names, Multiple Assignment, Variable Types	Youtube 2	Exercise 3
5	Fundamentals of Python - Tokens, Keywords, Literals, Operators, Identifiers & Comments	Python Lessons for Practice	Exercise 4
6	Data Types - Numbers, Sequence Type, Dictionary, Set, Type Conversion	Data Analysis with Python - by IBM	Exercise 5
7	Collection Module - String, List & Tuples, Sets, Dictionary & Different containers provided by collection module	Data Visualization with Python	Exercise 6
8	Control Flows - Indentation, If-Else & ELIF Statements, For, While & Nested Loops, Control statements & Patterns	Databases and SQL for Data Science with Python - by IBM	Exercise 7
9	Functions - Types of Functions, Arguments & it's Types, Scope of Variables, Built-in Functions	Statistics for Data Science with Python - by IBM	Exercise 8
10	Functions - Lambda Functions, Decorators, Generators	HackerRank - Practice
11	Arrays	Code With Harry - Python Notes & Tutorial	Exercise 9
12	Hash Tables / Hash Map	Python Cheatsheet - Code With Harry	Exercise 10
13	OOPs Concept - Class & Objects, Constructors, Destructors, Inheritance	Basic Python Projects - YouTube	Exercise 11
14	OOPs Concept - Polymorphism, Encapsulation	Project 1: Spotify Data Analysis using Python
15	OOPs Concept - Data Abstraction, Python Super Function	Project 2: Statistics for Data Science using Python
16	Exception Handling, File Handling		Exercise 12
17	Unit Testing in Python	:white_check_mark:

Prerequisite: Python Libraries for Data Science Roadmap 🗂️

Projects in Python

Sr.No. 🔢	Projects 👨‍💻	Reference Links :link:
Python Project 1	Spotify Data Analysis using Python	GitHub Project & Kaggle Notebook
Python Project 2	Boston Housing Data Analysis using Python	Project

Useful sites to learn Coding in Python :link:

YouTube Channels:

freeCodeCamp.org	Code With Harry, Programming With Harry	CodeBasics	Edureka	Gate Smashers	Jenny's Lectures	Simplilearn	Intellipaat

Other Learning Platforms:

JavaTpoint	TutorialsPoint	Geeks For Geeks	Code With Harry	GitHub	Kaggle	DataCamp	W3Schools	Guru99	Dev

For Certifications:

Coursera	Kaggle	Simplilearn	Great Learnings	Forage	Edureka	HackerRank	Udemy	Codechef	Upgrad	Udacity

For Coding Practice:

HackerRank	Leetcode	Kaggle	Codechef	Unstop	HackerEarth	Codeforces	Interviewbit	Google Dev

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For any queries/doubts 🔗 👇

Ankit Gupta