Lesson Index
- Lesson 1: Introduction to Python and Installation
- Lesson 2: Understanding Python Syntax and Running Scripts
- Lesson 3: Variables, Data Types, and Type Conversion
- Lesson 4: Working with Strings
- Lesson 5: Lists, Tuples, and Dictionaries
- Lesson 6: Conditional Logic (if/elif/else)
- Lesson 7: Loops (for, while)
- Lesson 8: Functions and Parameters
- Lesson 9: Modules and Packages
- Lesson 10: File Handling (read/write)
- Lesson 11: Error Handling with try/except
- Lesson 12: Object-Oriented Programming Basics
- Lesson 13: Classes, Objects, and Inheritance
- Lesson 14: Virtual Environments and Dependency Management
- Lesson 15: Working with External Libraries (pip)
- Lesson 16: Introduction to APIs and HTTP Requests
- Lesson 17: JSON Handling in Python
- Lesson 18: Working with Databases (SQLite)
- Lesson 19: Asynchronous Programming (async/await)
- Lesson 20: Building and Packaging a Small Python Project
- Lesson 21: Creating Executable Applications
- Lesson 22: Deploying Python Applications
- Lesson 23: Introduction to Automation and Scripting
- Lesson 24: Working with the OS and System Commands
- Lesson 25: Working with CSV and Excel Files
- Lesson 26: Introduction to Data Visualization (matplotlib)
- Lesson 27: Introduction to Data Analysis with pandas
- Lesson 28: Introduction to NumPy for Numerical Computing
- Lesson 29: Introduction to SciPy
- Lesson 30: Introduction to Machine Learning Concepts
- Lesson 31: Introduction to Neural Networks
- Lesson 32: Convolutional Neural Networks (CNNs)
- Lesson 33: Recurrent Neural Networks (RNNs)
- Lesson 34: Introduction to Transformers
- Lesson 35: Large Language Models (LLMs)
- Lesson 36: Prompt Engineering Basics
- Lesson 37: Building AI‑Powered Applications
- Lesson 38: Deploying and Scaling AI Systems
- Lesson 39: Monitoring, Retraining, and the Model Lifecycle
- Lesson 40: Ethics, Safety, and Responsible AI
- Lesson 41: Choosing the Right Programming Tools — PyCharm vs. VS Code