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Course Outline
Introduction to AI Agents
- Defining AI agents
- Classifications of AI agents: Reactive, proactive, and hybrid models
- Real-world implementation scenarios for AI agents
Core Design Principles
- Essential elements of an AI agent architecture
- Interaction between agents and their environments
- Foundations 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
- Tailoring agent behaviors
Advanced AI Agent Features
- Integrating natural language understanding capabilities
- Incorporating machine learning models
- Personalizing agent interactions and responses
Practical Applications
- AI agents in customer support services
- Virtual assistants and productivity enhancers
- Interactive educational platforms
Performance Enhancement
- Improving agent operational efficiency
- Considerations for system scalability
- Evaluating agent performance via KPIs
Ethical and Societal Impact
- Mitigating biases within AI agents
- Safeguarding privacy and data security
- Adherence to AI regulatory standards
Challenges and Future Outlook
- Limits in scalability and performance
- Ethical considerations in deploying AI agents
- Evolving trends in AI agent technology
Requirements
- Fundamental knowledge of artificial intelligence principles
- Basic proficiency in Python programming
Target Audience
- Individuals with a strong interest in AI
- Information technology professionals
14 Hours
