Course Outline
Introduction to Agentic AI
- What is Agentic AI?
- How it differs from traditional AI models
- Historical evolution and key breakthroughs
Core Capabilities of Agentic AI
- Autonomous decision-making and adaptability
- Long-term planning and self-improvement
- Multi-agent collaboration and communication
Real-World Applications of Agentic AI
- AI-powered automation in enterprises
- Agentic AI in finance, healthcare, and customer service
- Use cases in robotics and smart assistants
Benefits and Challenges of Agentic AI
- Enhancing efficiency and scalability in businesses
- Potential risks and limitations of autonomous AI
- Strategies for responsible AI development
Ethical and Security Considerations
- AI safety and risk mitigation strategies
- Addressing biases and accountability in Agentic AI
- Regulatory and governance frameworks
The Future of Agentic AI
- Trends in autonomous AI research and development
- How businesses can prepare for AI-driven transformation
- Scaling AI capabilities for real-world applications
Summary and Next Steps
Requirements
- Basic understanding of artificial intelligence
- Familiarity with AI applications in business or technology
Audience
- Business leaders exploring AI-driven automation
- Technology strategists analyzing AI adoption
- AI enthusiasts interested in autonomous AI systems
Testimonials (4)
Strong confirmation that current LLMs are deployable for customer projects when the proper setup is in place.
Oliver Fromm
Course - Agentic AI for Enterprise Applications
Machine Translated
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
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