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Course Outline

Introduction to AI Agents

  • Definition of AI agents
  • Types of AI agents: Reactive, proactive, and hybrid
  • Real-world applications of AI agents

Fundamental Design Principles

  • Core components of an AI agent
  • Interaction between agent and environment
  • Introduction to agent-based modeling

Constructing Simple AI Agents

  • Overview of tools and frameworks for AI agent development
  • Practical exercise: Building a basic chatbot using Rasa
  • Customizing agent behaviors

Advanced Capabilities of AI Agents

  • Incorporating natural language understanding
  • Integrating machine learning models
  • Personalizing agent responses

Practical Use Cases

  • Application of AI agents in customer service
  • Virtual assistants and personal productivity tools
  • Interactive educational tools

Performance Optimization

  • Improving agent efficiency
  • Scalability considerations
  • Evaluating agent success using KPIs

Ethical and Social Implications

  • Addressing biases in AI agents
  • Ensuring privacy and data security
  • Compliance with AI regulations

Challenges and Future Directions

  • Limitations regarding scalability and performance
  • Ethical considerations in AI agent deployment
  • Emerging trends in AI agent technology

Summary and Next Steps

Requirements

  • Foundational knowledge of artificial intelligence concepts
  • Familiarity with Python programming

Target Audience

  • AI enthusiasts
  • IT professionals
 14 Hours

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