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Duration 14 hours
Course Outline
Foundations of AI Agents
- Defining the concept of AI agents
- Categorization of agents: Reactive, proactive, and hybrid models
- Real-world applications of AI agents
Core Design Principles
- Essential structural components of an AI agent
- Mechanisms of interaction between agents and their environments
- Introduction to agent-based modeling techniques
Developing Elementary AI Agents
- Survey of development tools and frameworks for AI agents
- Practical exercise: Building a basic chatbot with Rasa
- Tailoring and customizing agent behaviors
Enhancing AI Agent Capabilities
- Integrating natural language understanding
- Connecting machine learning models to agent logic
- Refining response personalization
Real-World Use Cases
- Application of AI agents in customer support
- Virtual assistants and productivity enhancement tools
- Interactive tools for education
Optimizing Performance
- Strategies for improving agent efficiency
- Considerations for system scalability
- Evaluating agent success through KPIs
Ethical and Societal Impact
- Mitigating biases within AI agents
- Safeguarding privacy and data security
- Adherence to regulatory standards for AI
Challenges and Future Outlook
- Navigating limitations in scalability and performance
- Ethical considerations during AI agent deployment
- Emerging trends in AI agent technology
Requirements
- A foundational grasp of artificial intelligence principles
- Proficiency in Python programming
Target Audience
- Enthusiasts in the field of AI
- IT industry professionals
