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Course Outline
Foundations of AI Agents
- Defining the concept of AI agents
- Categorizations of AI agents: reactive, proactive, and hybrid models
- Real-world applications of AI agents in diverse scenarios
Core Design Frameworks
- Essential structural elements of an AI agent
- Managing interactions between agents and their environment
- Basics of agent-based modeling techniques
Developing Elementary AI Agents
- Survey of development tools and frameworks for AI agents
- Practical session: Constructing a basic chatbot utilizing Rasa
- Adjusting and customizing agent behavioral logic
Enhanced AI Agent Features
- Integrating natural language understanding capabilities
- Incorporating machine learning models into agent workflows
- Refining agent responses for personalization
Real-World Applications
- Deployment of AI agents in customer support contexts
- Use in virtual assistants and personal productivity enhancements
- Applications in interactive educational environments
Optimizing Performance
- Strategies for improving agent operational efficiency
- Considerations for system scalability
- Evaluating agent effectiveness using Key Performance Indicators (KPIs)
Ethical and Societal Considerations
- Mitigating biases inherent in AI agent designs
- Safeguarding user privacy and data security
- Adhering to relevant AI regulatory standards
Current Challenges and Future Trajectories
- Navigating constraints in scalability and performance
- Addressing ethical implications in AI agent deployment
- Identifying emerging trends in AI agent technology
Requirements
- A foundational grasp of artificial intelligence principles
- Proficiency in Python programming
Target Audience
- Individuals with a keen interest in AI
- Professionals in the IT sector
14 Hours
