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Duration 21 hours
Course Outline
Introduction to Agentic AI Systems
- Defining the scope and capabilities of Agentic AI
- Distinguishing between rule-based AI and autonomous AI paradigms
- Exploring relevant use cases and industry-specific applications
Designing Agentic AI Architectures
- Utilizing frameworks and tools for building autonomous AI solutions
- Creating AI agents with goal-oriented capabilities
- Incorporating memory, context-awareness, and adaptive mechanisms
Building AI Agents with Python and APIs
- Constructing functional AI agents
- Connecting AI models to external data sources
- Processing API responses and enhancing agent interaction quality
Optimizing Multi-Agent Collaboration
- Designing agents for both cooperative and competitive task environments
- Managing inter-agent communication and effective task delegation
- Scaling multi-agent systems for deployment in real-world applications
Refining Decision-Making in Agentic AI
- Applying reinforcement learning and self-improving AI agent strategies
- Executing planning, reasoning, and long-term goal management
- Striking a balance between automation and human oversight
Security, Ethics, and Compliance in Agentic AI
- Mitigating biases and ensuring responsible AI deployment practices
- Implementing security measures for AI-driven decision-making processes
- Considering regulatory frameworks for autonomous AI systems
Emerging Trends in Agentic AI
- Exploring advancements in AI autonomy and self-learning systems
- Expanding agent capabilities through multimodal learning techniques
- Preparing for the next generation of autonomous AI developments
Recap and Recommended Next Steps
Requirements
- A solid foundation in core AI and machine learning concepts
- Proficiency in Python programming
- Working knowledge of API-based AI model integration
Target Audience
- AI engineers focused on developing autonomous AI systems
- ML researchers investigating multi-agent AI frameworks
- Developers tasked with implementing AI-driven automation solutions
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
