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