Complete Python Roadmap (Divided into 30 Modules) 🔥💻

Categories	Modules
Core Concepts 🌟	Introduction and Basics of Python Operators Conditional Statements While Loops Lists Strings
Control Flow 🌐	For Loops Functions Dictionary Tuples Set
Data Structures 🏗️	Data Structures Higher-Order Functions
Object-Oriented Programming 🧬	Object-Oriented Programming
File Handling and Modules 📁	File Handling Exception Handling Regular Expression Modules and Packages
Web Development 🌐	Virtual Environment Web Application Project
Version Control and Deployment 🚀	Git and GitHub Deployment
Data Analysis and Visualization 📊	Python Package Manager Python with MongoDB Database Building API Statistics with NumPy Data Analysis with Pandas Data Visualization with Matplotlib
Extras	What to do Now?

---

Core Concepts

1. Introduction and Basics of Python

• Installation
• Python Org, Python 3
• Variables
• Print function
• Input from user
• Data Types
• Type Conversion
• First Program

2. Operators

• Arithmetic Operators
• Relational Operators
• Bitwise Operators
• Logical Operators
• Assignment Operators
• Compound Operators
• Membership Operators
• Identity Operators

3. Conditional Statements

• If Else
• If
• Else
• El If (else if)
• If Else Ternary Expression

4. While Loops

• While loop logic building
• Series based Questions
• Break
• Continue
• Nested While Loops
• Pattern-Based Questions
• pass
• Loop else

5. Lists

• List Basics
• List Operations
• List Comprehensions / Slicing
• List Methods

6. Strings

• String Basics
• String Literals
• String Operations
• String Comprehensions / Slicing
• String Methods

---

Control Flow

7. For Loops

• Range function
• For loop
• Nested for Loops
• Pattern-Based Questions
• Break
• Continue
• Pass
• Loop else

8. Functions

• Definition
• Call
• Function Arguments
• Default Arguments
• Docstrings
• Scope
• Special functions Lambda, Map, and Filter
• Recursion
• Functional Programming and Reference Functions

9. Dictionary

• Dictionaries Basics
• Operations
• Comprehensions
• Dictionaries Methods

10. Tuples

• Tuples Basics
• Tuples Comprehensions / Slicing
• Tuple Functions
• Tuple Methods

11. Set

• Sets Basics
• Sets Operations
• Union
• Intersection
• Difference and Symmetric Difference

---

Data Structures

17. Data Structures

• Stack
• Queue
• Linked Lists
• Sorting
• Searching
  • Linear Search
  • Binary Search

18. Higher-Order Functions

• Function as a parameter
• Function as a return value
• Closures
• Decorators
• Map, Filter, Reduce Functions

---

Object-Oriented Programming

12. Object-Oriented Programming

• Classes
• Objects
• Method Calls
• Inheritance and Its Types
• Overloading
• Overriding
• Data Hiding
• Operator Overloading

---

File Handling and Modules

13. File Handling

• File Basics
• Opening Files
• Reading Files
• Writing Files
• Editing Files
• Working with different extensions of file
• With Statements

14. Exception Handling

• Common Exceptions
• Exception Handling
  • Try
  • Except
  • Try except else
  • Finally
  • Raising exceptions
  • Assertion

15. Regular Expression

• Basic RE functions
• Patterns
• Meta Characters

16. Modules and Packages

• Different types of modules
• Inbuilt modules
  • OS
  • Sys
  • Statistics
  • Math
  • String
  • Random
• Create your own module
• Building Packages

---

Web Development

20. Virtual Environment

• Virtual Environment Setup

21. Web Application Project

• Flask
• Project Structure
• Routes
• Templates
• Navigations

---

Version Control and Deployment

22. Git and GitHub

• Git - Version Control System
• GitHub Profile building
• Manage your work on GitHub

23. Deployment

• Heroku Deployment
• Flask Integration

---

Data Analysis and Visualization

24. Python Package Manager

• What is PIP?
• Installation
• PIP Freeze
• Creating Your Own Package
• Upload it on PIP

25. Python with MongoDB Database

• SQL and NoSQL
• Connecting to MongoDB URI
• Flask application and MongoDB integration
• CRUD Operations
• Find
• Delete
• Drop

26. Building API

• API (Application Programming Interface)
• Building API
• Structure of an API
• PUT
• POST
• DELETE
• Using Postman

27. Statistics with NumPy

• Statistics
• NumPy basics
• Working with Matrix
• Linear Algebra operations
• Descriptive Statistics

28. Data Analysis with Pandas

• Data Analysis basics
• Data frame operations
• Working with 2-dimensional data
• Data Cleaning
• Data Grouping

29. Data Visualization with Matplotlib

• Matplotlib Basics
• Working with plots
• Plot
• Pie Chart
• Histogram

Extras

30. What to do Now?

• Project Building

---

LinkedIn    Website    Facebook    Email