Saturday, April 12, 2025

Released a new ebook "Python for AI Developers: A Beginner's Guide to Artificial Intelligence Programming"


I have created an ebook with the title "Python for AI Developers: A Beginner's Guide to Artificial Intelligence Programming"

You can buy it from here. This ebook is included in the AI Course, which you can get with a discount using the coupon code QPT.



Find below the chapters of this ebook.

 Chapter 1: Introduction to Python for AI

๐Ÿ”น 1.1 Why Python for AI Development? 

๐Ÿ”น 1.2 Installing Python and Setting Up Your Development Environment 

๐Ÿ”น 1.3 Introduction to Jupyter Notebooks and Google Colab 

๐Ÿ”น 1.4 Python Basics Recap: Let’s Get Coding! 

๐ŸŽฏ Hands-On Practice 

๐Ÿš€ What’s Next? 

Chapter 2: Core Python Programming 

๐Ÿ”น 2.1 Control Flow: If-Else, Loops 

๐Ÿ”น 2.2 Functions and Modules 

๐Ÿ”น 2.3 Object-Oriented Programming (OOP) in Python 

๐Ÿ”น 2.4 Exception Handling 

๐Ÿงช Practice Time 

๐Ÿš€ What’s Next? 

Chapter 3: Essential Python Libraries for AI 

๐Ÿ”น 3.1 NumPy: Handling Arrays and Matrices 

๐Ÿ”น 3.2 Pandas: Data Analysis and DataFrames 

๐Ÿ”น 3.3 Matplotlib & Seaborn: Data Visualization 

๐Ÿ”น 3.4 Scikit-learn: Introduction to Machine Learning 

๐Ÿงช Practice Time 

๐Ÿš€ What’s Next? 

Chapter 4: Working with Data

๐Ÿ”น 4.1 Loading and Preprocessing Datasets

๐Ÿ”น 4.2 Handling Missing Data and Outliers

๐Ÿ”น 4.3 Feature Engineering and Scaling

๐Ÿงช Practice Time 

๐Ÿ“Œ Quick Tips for Better Data Handling

๐Ÿš€ What’s Next?

Chapter 5: Introduction to Machine Learning with Python

๐Ÿ”น 5.1 Supervised vs. Unsupervised Learning

๐Ÿ”น 5.2 Building a Simple Machine Learning Model with Scikit-learn

๐Ÿ”น 5.3 Evaluating Model Performance

๐Ÿ› ️ Other Useful Metrics

๐Ÿ’ก Pro Tips 

๐Ÿงช Practice Time

๐Ÿš€ What’s Next?

Chapter 6: Deep Learning with Python 

๐Ÿ”น 6.1 Introduction to Neural Networks

๐Ÿ”น 6.2 Using TensorFlow and PyTorch 

๐Ÿ”ธ 6.3 Building a Simple Neural Network 

๐Ÿ”น 6.4 Training and Evaluating Deep Learning Models

๐Ÿ”น Bonus: PyTorch Version (Optional for Advanced Users) 

๐Ÿงช Practice Time 

๐Ÿ“Œ Quick Tips 

๐Ÿš€ What’s Next? 

Chapter 7: Natural Language Processing (NLP) with Python 

๐Ÿ”น 7.1 Tokenization and Text Processing 

๐Ÿ”น 7.2 Word Embeddings and Transformers 

๐Ÿ”น 7.3 Building an NLP Model with Hugging Face

๐Ÿงช Practice Time 

๐Ÿ“Œ Quick Tips 

๐Ÿš€ What’s Next? 

Chapter 8: Computer Vision with Python 

๐Ÿ”น 8.1 Working with OpenCV

๐Ÿ”น 8.2 Image Classification with TensorFlow/Keras

๐Ÿ”น 8.3 Object Detection Basics

๐Ÿงช Practice Time

๐Ÿ“Œ Quick Tips

๐Ÿš€ What’s Next? 

Chapter 9: AI Model Deployment 

๐Ÿ”น 9.1 Saving and Loading AI Models 

๐Ÿ”น 9.2 Deploying Models with Flask 

๐Ÿ”น 9.3 Deploying with FastAPI (Modern & Fast ๐Ÿš€) 

๐Ÿ”น 9.4 Running AI Models in the Cloud 

๐Ÿงช Practice Time 

๐Ÿ“Œ Quick Tips 

๐Ÿš€ What’s Next? 

Chapter 10: Advanced AI Topics & Next Steps 

๐Ÿ”น 10.1 Reinforcement Learning (RL) Overview 

๐Ÿ”น 10.2 Generative AI & Large Language Models (LLMs) 

๐Ÿ”น 10.3 Trends and Future of AI 

๐Ÿ”น 10.4 Career Roadmap in AI 

๐Ÿงญ Your Learning Journey: What’s Next? 

๐Ÿงช Final Challenge 

๐Ÿง  Final Thoughts 

You can buy it from here. This ebook is included in the AI Course, which you can get with a discount using the coupon code QPT.



No comments:

Search This Blog