Python with Artificial Intelligence is a practical and comprehensive guide to learning Artificial Intelligence using Python. The book takes readers from Python programming fundamentals to Machine Learning, Deep Learning, Natural Language Processing, and Generative AI.

Readers will learn how to use popular Python libraries and frameworks to process data, build intelligent systems, train Machine Learning models, work with neural networks, and develop practical AI applications.

The book follows a step-by-step approach, combining theoretical concepts with practical Python examples and real-world projects. It is designed to help beginners and developers build a strong foundation in Artificial Intelligence and understand how modern AI applications are developed using Python.

What You Will Learn
Python programming fundamentals for Artificial Intelligence
Variables, data types, operators, and control statements
Functions, modules, packages, and exception handling
Lists, tuples, sets, and dictionaries
Object-Oriented Programming with Python
File handling and JSON processing
Python libraries for AI and Data Science
NumPy for numerical computing
Pandas for data analysis
Matplotlib and Seaborn for data visualization
Introduction to Artificial Intelligence
AI concepts, applications, and real-world use cases
Types of Artificial Intelligence
Machine Learning fundamentals
Supervised and Unsupervised Learning
Data preprocessing and feature engineering
Linear and Logistic Regression
K-Nearest Neighbors
Decision Trees and Random Forest
Support Vector Machines
Naive Bayes
K-Means Clustering
Principal Component Analysis
Machine Learning model evaluation
Scikit-Learn for AI development
Introduction to Deep Learning
Neural Networks and Artificial Neural Networks
Activation functions and optimization
Forward propagation and backpropagation
Introduction to CNN, RNN, and LSTM
Natural Language Processing with Python
Text preprocessing and tokenization
Text classification and sentiment analysis
Introduction to Transformers
Introduction to Large Language Models (LLMs)
Generative AI fundamentals
Prompt Engineering
AI-powered text generation
Embeddings and semantic search
Retrieval-Augmented Generation (RAG)
Introduction to AI Agents
Tool calling and AI automation
Working with modern AI APIs and Python libraries
Building intelligent applications with Python
AI model evaluation and deployment
Real-world Artificial Intelligence projects