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AI Agents: From Theory to Practice
Introduction
Introduction to the AI Agent Course
Module 1: Foundations of AI Agents
1.1 An Introduction to AI Agents
1.2 Historical Evolution of AI Agents
1.3 AI Agents: A Synthesis of AI and Agent Design
1.4 Fundamental Principles of AI Agents
1.5 Examples and Analogies
Module 2: A Detailed Breakdown of AI Agent Architecture
2.1 Essential Components and Interactions
2.2 Perception Module
2.3 Action Module
2.4 Memory Module
2.5 Tools
2.6 Architectural Approaches: Single-Agent vs Multi-Agent
2.7 Specific Examples of Component Interactions
Module 3: AI Agent Capabilities and Types
3.1 An Examination of AI Agent Types and Examples
3.2 How to Classify AI Agent Types
3.3 Detailed Characteristics and Example of Each Agent Type
3.4 Trending Real-world Applications of AI Agents 2024-2025
3.5 A Synthesis of Advanced AI Agent Systems
3.6 Enterprise Application Requirements and Integration Practices
Module 4: Development, Applications, and Industry Use Cases
4.1 Prominent LLM-Based Agents
4.2 Popular Industry Use Cases of AI Agents
4.3 Use Cases: Manufacturing, Retail, Logistics, & Entertainment
4.4 Popular Frameworks for Developing AI Agents
4.5 How to Develop an AI Agent: A Step-by-Step Guide
4.6 Design, Develop, Deploy, and Monitor
Module 5: Development Considerations, Challenges, Future Prospects
5.1 Key Development Considerations: Costs & Technologies
5.2 Challenges, Limitations in AI Agent Development
5.3 Best Practices
5.4 Future Prospects for AI Agents
5.5 Potential Areas of Transformation
Conclusion
Congratulations!
3.4 Trending Real-world Applications of AI Agents 2024-2025
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