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Course Outline
Fundamentals of AI Agents
- Defining AI agents: What they are and how they function.
- Categorization of AI agents: Reactive, proactive, and hybrid models.
- Real-world applications of AI agents in various scenarios.
Core Design Principles
- Essential components that constitute an AI agent.
- Understanding the interaction between agents and their environments.
- An introduction to agent-based modeling techniques.
Developing Basic AI Agents
- Survey of tools and frameworks for AI agent development.
- Practical session: Building a basic chatbot using Rasa.
- Methods for customizing agent behavior.
Enhancing AI Agent Capabilities
- Integrating natural language understanding features.
- Incorporating machine learning models into agent workflows.
- Tailoring agent responses for personalization.
Real-World Applications
- The role of AI agents in customer service operations.
- Virtual assistants and tools for personal productivity.
- Interactive solutions for educational contexts.
Optimizing Performance
- Strategies for improving agent efficiency.
- Key considerations for scalability.
- Evaluating agent success through KPIs.
Ethical and Societal Impact
- Mitigating biases within AI agents.
- Safeguarding privacy and data security.
- Adhering to AI regulatory standards.
Challenges and Future Trajectories
- Addressing limitations in scalability and performance.
- Navigating ethical considerations in AI agent deployment.
- Emerging trends shaping the future of AI agent technology.
Requirements
- Fundamental knowledge of artificial intelligence concepts
- Proficiency in Python programming
Intended Audience
- Individuals with a keen interest in AI
- Professionals in the IT sector
14 Hours
