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Course Outline

Introduction to AI Agents

  • Defining AI agents
  • Categorizing AI agents: reactive, proactive, and hybrid models
  • Real-world applications of AI agents

Foundational Design Principles

  • Core components of an AI agent
  • Interactions between agents and their environments
  • Basics of agent-based modeling

Developing Simple AI Agents

  • Survey of development tools and frameworks for AI agents
  • Practical exercise: Building a fundamental chatbot with Rasa
  • Tailoring agent behaviors

Advanced AI Agent Features

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

Practical Applications

  • Utilizing AI agents in customer service
  • Virtual assistants and personal productivity enhancements
  • Interactive educational platforms

Optimizing Performance

  • Improving agent efficiency
  • Considerations for scalability
  • Evaluating agent success through KPIs

Ethical and Social Considerations

  • Mitigating biases in AI agents
  • Safeguarding privacy and data security
  • Adhering to AI regulatory standards

Challenges and Future Trajectories

  • Addressing scalability and performance constraints
  • Ethical dimensions of AI agent deployment
  • Emerging trends in AI agent technology

Requirements

  • A foundational grasp of artificial intelligence principles
  • Proficiency in Python programming

Target Audience

  • Individuals passionate about AI
  • IT industry professionals
 14 Hours

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