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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

  • Essential components of an AI agent
  • Interactions between agents and their environment
  • Overview of agent-based modeling

Developing Basic AI Agents

  • Survey of tools and frameworks for AI agent creation
  • Practical exercise: Building a basic chatbot with Rasa
  • Modifying and customizing agent behavior

Enhanced AI Agent Features

  • Incorporating natural language understanding
  • Integration of machine learning models
  • Personalizing agent interactions and responses

Practical Applications

  • Implementing AI agents in customer service
  • Virtual assistants and productivity-enhancing tools
  • Interactive educational platforms

Performance Optimization

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

Ethical and Social Impact

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

Challenges and Future Trajectories

  • Limitations regarding scalability and performance
  • Ethical aspects of deploying AI agents
  • Emerging trends in AI agent technology

Requirements

  • Foundational knowledge of artificial intelligence principles
  • Proficiency in Python programming

Target Audience

  • AI practitioners and enthusiasts
  • IT specialists and professionals
 14 Hours

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