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Course Outline
Introduction to Agentic AI Systems
- Defining Agentic AI and its inherent capabilities
- Distinguishing between rule-based AI and autonomous AI architectures
- Exploring use cases and industry-specific applications
Designing Agentic AI Architectures
- Utilizing frameworks and tools for building autonomous AI
- Creating AI agents with goal-oriented functionalities
- Incorporating memory, context awareness, and adaptive behaviors
Creating AI Agents using Python and APIs
- Constructing functional AI agents
- Linking AI models with external data sources
- Processing API responses to enhance agent interactions
Improving Multi-Agent Collaboration
- Designing agents for both cooperative and competitive scenarios
- Overseeing agent communication and task distribution
- Scaling multi-agent systems for production environments
Strengthening Decision-Making in Agentic AI
- Applying reinforcement learning and self-improving mechanisms
- Executing planning, reasoning, and long-term goal strategies
- Maintaining a balance between automation and human supervision
Security, Ethics, and Compliance in Agentic AI
- Mitigating biases to ensure responsible AI deployment
- Implementing security protocols for AI-driven decisions
- Navigating regulatory frameworks for autonomous AI systems
Emerging Trends in Agentic AI
- Advancements in AI autonomy and self-learning systems
- Expanding agent capabilities through multimodal learning
- Preparing for the next wave of autonomous AI technologies
Conclusion and Future Directions
Requirements
- Foundational knowledge of AI and machine learning concepts
- Proficiency in Python programming
- Experience with integrating AI models via APIs
Target Audience
- AI engineers focused on creating autonomous AI systems
- ML researchers investigating multi-agent AI frameworks
- Developers building AI-driven automation solutions
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
