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Course Outline
Introduction to Agentic AI
- Defining Agentic AI
- Key distinctions from traditional AI models
- Historical evolution and pivotal breakthroughs
Core Capabilities of Agentic AI
- Autonomous decision-making and adaptability
- Long-term planning and self-improvement mechanisms
- Multi-agent collaboration and communication
Real-World Applications of Agentic AI
- AI-driven automation in enterprise environments
- Applications in finance, healthcare, and customer service
- Use cases involving robotics and smart assistants
Benefits and Challenges of Agentic AI
- Improving efficiency and scalability for businesses
- Potential risks and limitations of autonomous AI
- Strategies for fostering responsible AI development
Ethical and Security Considerations
- AI safety and risk mitigation strategies
- Addressing biases and ensuring accountability in Agentic AI
- Relevant regulatory and governance frameworks
The Future of Agentic AI
- Emerging trends in autonomous AI research and development
- How businesses can prepare for AI-driven transformation
- Scaling AI capabilities for practical applications
Summary and Next Steps
Requirements
- Foundational knowledge of artificial intelligence
- Familiarity with the use of AI in business or technology contexts
Target Audience
- Business leaders investigating AI-driven automation solutions
- Technology strategists evaluating AI adoption strategies
- AI enthusiasts keen on learning about autonomous AI systems
7 Hours
Testimonials (4)
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
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Autonomous Decision-Making with Agentic AI
practical exercises
