AI Fundamentals
AI Fundamentals
Understanding the Core Concepts, Technologies, and Business Impact of Artificial Intelligence
About the Book
AI Fundamentals is a comprehensive guide designed to help readers understand the essential principles, technologies, and real-world applications of artificial intelligence. The book covers key AI concepts such as machine learning, deep learning, natural language processing, and neural networks, providing a structured approach to understanding how AI systems work. It also explores the role of big data in AI development, the importance of algorithmic transparency, and the ethical considerations surrounding AI adoption. Whether you are a business leader, a data scientist, or an enthusiast looking to deepen your knowledge, this book offers a clear and practical introduction to the field.
Beyond technical insights, AI Fundamentals focuses on the strategic value of AI for organizations. It highlights how AI can drive business growth, improve decision-making, and create competitive advantages. Real-world case studies, such as Netflix’s AI-driven recommendation engine and AI-powered customer service automation, demonstrate how companies are successfully leveraging AI for innovation and efficiency. The book also provides guidance on building an AI business case, measuring return on investment, and implementing responsible AI practices. By bridging the gap between theory and application, AI Fundamentals equips readers with the knowledge to navigate the AI-driven future confidently.
About the Author
Table of Contents
- Introduction
- The AI Revolution in Business
- Why Every Business Professional Needs AI Literacy
- AI: Hype vs. Reality
- How to Use This Book
- AI Certifications
- Final Thoughts
- 1. Understanding Artificial Intelligence
- 1.1 What AI Is and Why It Matters
- 1.2 AI in the Enterprise
- 1.3 Defining AI: From Concept to Reality
- 1.4 The Evolution of AI: Key Milestones and Breakthroughs
- 1.5 Narrow AI vs. General AI vs. Superintelligence
- 1.6 The AI Ecosystem: Key Technologies and Players
- 1.7 AI’s Role in Digital Transformation
- 1.8 Chapter Summary: Understanding Artificial Intelligence
- 2. Core AI Technologies and How They Work
- 2.1 Understanding How AI Works
- 2.2 Machine Learning
- 2.3 Deep Learning
- 2.4 Natural Language Processing
- 2.5 Computer Vision
- 2.6 Chapter Summary: Core AI Technologies and How They Work
- 3. Generative AI and Large Language Models
- 3.1 Introduction to Generative AI and LLMs
- 3.2 Evolution of Large Language Models
- 3.3 How Generative AI Works
- 3.4 Key Applications of Generative AI
- 3.5 Popular Large Language Models
- 3.6 Core Techniques in LLMs
- 3.7 Future Directions and Innovations
- 3.8 Chapter Summary: Generative AI and Large Language Models
- 4. Multimodal AI - Images and Videos
- 4.1 Introduction to Multimodal AI
- 4.2 Core Components of Multimodal AI
- 4.3 Key Models in Multimodal AI
- 4.4 Chapter Summary: Multimodal AI – Images and Videos
- 5. Working with AI in the organization
- 5.1 AI in the Enterprise: Understanding Benefits and Risk
- 5.2 The Business Case
- 5.3 AI Implementation
- 5.4 Risks in AI Solutions
- 5.5 AI Governance and Responsible AI Leadership
- 5.6 Chapter Summary
- Introduction
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