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Course Outline

Introduction to AI Agents

  • What are AI agents?
  • Types of AI agents: Reactive, proactive, and hybrid.
  • Real-world applications of AI agents.

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

  • Foundational understanding of artificial intelligence concepts.
  • Familiarity with Python programming.

Target Audience

  • AI enthusiasts.
  • IT professionals.
 14 Hours

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