AI Systems - Foundation Track

⏱️ Estimated reading time: 3 minutes

This track covers the theoretical underpinnings of agentic systems, providing you with the conceptual foundation needed to understand and design intelligent agents.

Table of Contents

Chapter	Title	Description
Chapter 1	Fundamentals of Generative AI	Core principles, models, and applications of generative AI
Chapter 2	Principles of Agentic Systems	Understanding agency, architectures, and system design
Chapter 3	Essential Components of Intelligent Agents	Core components: perception, memory, reasoning, and action
Chapter 4	Reflection and Introspection in Agents	Meta-cognitive capabilities and self-improvement mechanisms
Chapter 5	Enabling Tool Use and Planning in Agents	Integration of external tools and planning capabilities
Chapter 6	Exploring the Coordinator, Worker, and Delegator Approach	Multi-agent coordination patterns and architectures
Chapter 7	Effective Agentic System Design Techniques	Best practices for designing robust agent systems
Chapter 8	Building Trust in Generative AI Systems	Transparency, explainability, and trust-building strategies
Chapter 9	Managing Safety and Ethical Considerations	Safety frameworks and ethical AI development
Chapter 10	Common Use Cases and Applications	Real-world applications and case studies
Chapter 11	Conclusion and Future Outlook	Synthesis and future directions in agentic AI

Learning Path

Start with Chapter 1 to build foundational knowledge of generative AI, then progress through each chapter sequentially. Each chapter builds upon concepts from previous chapters while introducing new theoretical frameworks and design principles.

Prerequisites

• Basic understanding of machine learning concepts
• Familiarity with artificial intelligence fundamentals
• Programming experience (helpful but not required for theoretical understanding)

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Ready to begin? Start with Chapter 1: Fundamentals of Generative AI →