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Course Outline
Introduction to Agentic AI Systems
- Defining Agentic AI and its capabilities.
- Key distinctions between rule-based AI and autonomous AI.
- Real-world use cases and industry applications.
Architecting Agentic AI Systems
- Frameworks and tools for developing autonomous AI.
- Designing goal-driven AI agents.
- Implementing memory, context-awareness, and adaptability features.
Developing AI Agents with Python and APIs
- Constructing AI agents.
- Integrating AI models with external data sources.
- Managing API responses and enhancing agent interactions.
Optimizing Multi-Agent Collaboration
- Designing AI agents for cooperative and competitive scenarios.
- Facilitating agent communication and task delegation.
- Scaling multi-agent systems for real-world deployment.
Enhancing Decision-Making in Agentic AI
- Leveraging reinforcement learning for self-improving AI agents.
- Executing planning, reasoning, and long-term goal achievement.
- Balancing automation with necessary human oversight.
Security, Ethics, and Compliance in Agentic AI
- Mitigating biases and ensuring responsible AI deployment.
- Implementing security measures for AI-driven decision-making.
- Addressing regulatory considerations for autonomous AI systems.
Future Trends in Agentic AI
- Advancements in AI autonomy and self-learning systems.
- Expanding AI agent capabilities through multimodal learning.
- Preparing for the next generation of autonomous AI.
Summary and Next Steps
Requirements
- Foundational understanding of AI and machine learning concepts.
- Proficiency in Python programming.
- Familiarity with integrating API-based AI models.
Target Audience
- AI engineers specializing in autonomous AI systems.
- ML researchers investigating multi-agent AI frameworks.
- Developers focused on implementing AI-driven automation.
21 Hours
Testimonials (3)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
