Course Outline

Introduction to AI Agents

  • What are AI agents?
  • Types of AI agents: Reactive, proactive, and hybrid
  • Applications of AI agents in real-world scenarios

Basic Design Principles

  • Key components of an AI agent
  • Agent-environment interaction
  • Introduction to agent-based modeling

Building Simple AI Agents

  • Overview of tools and frameworks for AI agent development
  • Hands-on: Creating a basic chatbot using Rasa
  • Customizing agent behaviors

Advanced AI Agent Capabilities

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

Practical Use Cases

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

Performance Optimization

  • Enhancing agent efficiency
  • Scalability considerations
  • Measuring agent success with KPIs

Ethical and Social Implications

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

Challenges and Future Directions

  • Scalability and performance limitations
  • Ethical considerations in AI agent deployment
  • Emerging trends in AI agent technology

Summary and Next Steps

Requirements

  • Basic understanding of artificial intelligence concepts
  • Familiarity with Python programming

Audience

  • AI enthusiasts
  • IT professionals
 14 Hours

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