Basic Python Topics:

1. Introduction to Python
   • What is Python?
   • History of Python
   • Python 2 vs. Python 3
2. Setting up Python
   • Installing Python
   • Using an Integrated Development Environment (IDE)
3. Variables and Data Types
   • Variables and Assignments
   • Numeric Data Types (int, float)
   • Strings (str)
   • Lists
   • Tuples
   • Dictionaries
4. Basic Operators
   • Arithmetic Operators
   • Comparison Operators
   • Logical Operators
5. Control Flow
   • Conditional Statements (if, elif, else)
   • Loops (for, while)
   • Break and Continue statements
6. Functions
   • Defining Functions
   • Parameters and Arguments
   • Return Statements
   • Scope and Lifetime of Variables
7. Data Structures
   • Lists, Tuples, and Dictionaries (in-depth)
   • List Comprehensions
   • Sets
   • Stacks and Queues
8. File Handling
   • Reading and Writing Files
   • File Modes
   • Working with CSV and JSON

Intermediate Python Topics:

9. Object-Oriented Programming (OOP)
   • Classes and Objects
   • Inheritance
   • Polymorphism
   • Encapsulation
   • Abstraction
10. Error Handling and Exception Handling
    • Try, Except, Finally blocks
    • Custom Exceptions
11. Modules and Packages
    • Importing Modules
    • Creating and Using Packages
    • The __init__.py file
12. Functional Programming
    • Lambda Functions
    • Map, Filter, and Reduce
    • Closures and Decorators
13. Regular Expressions (Regex)
    • Pattern Matching
    • Searching and Replacing
    • Regex Groups
14. Working with Dates and Times
    • datetime module
    • Formatting Dates and Times
    • Time Zones

Advanced Python Topics:

15. Concurrency and Multithreading
    • Threading vs. Multiprocessing
    • threading and multiprocessing modules
    • Locks and Semaphores
16. Networking and Socket Programming
    • Creating Sockets
    • TCP and UDP Communication
    • Web Scraping
17. Database Connectivity
    • Connecting to Databases
    • SQL Queries with Python
    • Object-Relational Mapping (ORM) with libraries like SQLAlchemy
18. Web Development
    • Introduction to Web Frameworks (e.g., Flask, Django)
    • Creating Web Applications
    • RESTful APIs
19. Machine Learning and Data Science with Python
    • Libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch
    • Data Visualization (matplotlib, seaborn)
    • Machine Learning Algorithms
20. Advanced Topics in Python
    • Metaclasses
    • Decorators with Arguments
    • Context Managers (the with statement)
    • Garbage Collection and Memory Management
21. Testing and Debugging
    • Unit Testing with unittest and pytest
    • Debugging Techniques
    • Profiling Python Code
22. Performance Optimization
    • Identifying Bottlenecks
    • Using Profilers and Performance Tools
    • Optimizing Code