This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models.

The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered.

The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable.

Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence.

Key Learnings

• Explore Python basics and AI integration for real-world application and career advancement.
• Experience the power of Python in AI with practical machine learning techniques.
• Practice Python's deep learning tools for innovative AI solution development.
• Dive into NLP with Python to revolutionize data interpretation and communication strategies.
• Simple yet practical understanding of reinforcement learning for strategic AI decision making.
• Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI.
• Harness Python's capabilities for creating AI applications with a focus on fairness and bias.

Table of Content

1. Introduction to Artificial Intelligence
2. Python for AI
3. Data as Fuel for AI
4. Machine Learning Foundation
5. Essentials of Deep Learning
6. NLP and Computer Vision
7. Hands-on Reinforcement Learning
8. Ethics to AI