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Duration 14 hours
Course Outline
Introduction to AI Agents
- Defining AI agents
- Categories of AI agents: Reactive, proactive, and hybrid
- Real-world applications of AI agents
Core Design Principles
- Essential components of an AI agent
- Interactions between agents and their environment
- Overview of agent-based modeling
Developing Simple AI Agents
- Review of tools and frameworks for AI agent development
- Practical exercise: Building a basic chatbot with Rasa
- Modifying and customizing agent behaviors
Advanced AI Agent Features
- Integrating natural language understanding
- Embedding machine learning models
- Tailoring agent responses for personalization
Real-World Applications
- Deploying AI agents in customer service
- Virtual assistants and personal productivity applications
- Interactive learning platforms
Optimizing Performance
- Improving agent efficiency
- Considerations for scalability
- Evaluating agent success through KPIs
Ethical and Societal Impact
- Mitigating biases in AI agents
- Safeguarding privacy and data security
- Adhering to AI regulatory standards
Challenges and Future Prospects
- Limitations regarding scalability and performance
- Ethical implications of AI agent deployment
- Emerging trends in AI agent technology
Requirements
- A foundational understanding of artificial intelligence concepts
- Proficiency in Python programming
Target Audience
- Enthusiasts of artificial intelligence
- IT professionals
