AI
Developing Agentic AI Systems
Developing Agentic AI Systems will help you stay on the cutting edge of AI. This course is an intensive three-day workshop designed for developers already proficient with LLM systems who are ready to take their skills to the next level. Participants will transcend conventional LLM applications, learning to architect, build, and deploy sophisticated autonomous agents. Along the way, they’ll gain mastery over the intricate architectures of intelligent agents, navigate the dynamic ecosystem of specialized tools, using advanced techniques to build secure, robust, and effective agentic systems. Emerge equipped to engineer the next generation of intelligent solutions, commanding newfound capabilities to address complex challenges with unprecedented autonomy. Participants will also master the architecture of intelligent agent teams, leverage specialized frameworks, and utilize effective communication protocols.
Duration
3 days (with optional 4th day)
Audience
Developers, Data Scientists, Data Engineers, Machine Learning Engineers, MLOps professionals, DevOps professionals.
prerequisites
Participants should have solid skills in Python, basic experience with machine learning, and solid understanding of LLMs and LLM systems.
Developing Agentic AI Systems ensures participants are able to:
- Understand the architecture of LLM agents and their core components Navigate the ecosystem of
libraries, utilities, and models for agentic AI Acquire hands-on experience building and evaluating
LLM agents - Develop practical knowledge to build and test agentic systems for maximum robustness Learn how to
optimize agent prompts and sampling parameters for greater performance Build the skills and
understanding to develop agentic LLM solutions - Understand the fundamental principles and mechanisms of multi-agent AI, including various
frameworks, architectures, and inter-agent communication protocols. - Gain experience designing and implementing specialized AI agents, and orchestrating their
collaboration within multi-agent systems to tackle complex tasks. - Become familiar with the parallels between multi-agent AI and common engineering concepts, such as
asynchronous programming and zero-trust.
Day 1: Foundations for Agentic Systems
1. Introduction to Agentic AI
2. Agentic AI Ecosystem
3. LLM Tools and Structured Output
4. Agent Memory, Observation and Planning
Day 2: Practical Design of Agentic Systems
5. Communication Protocols for Agents
6. Agentic Prompting Strategies
7. Safety Mechanisms for Agents
8. Testing and Diagnostics for Agents
Day 3: Designing Multi-Agent Systems
9. Overview of Multi-Agent AI
10. Frameworks for Building Multi-Agent Systems
11. Multi-Agent Architectures and Communications
12. Agent Specialization
Day 4 (optional): Building For Production Environments
13. Response Consistency and Reliability
14. Observation and Intervention for Multi-Agent Systems
15. Fault Tolerance and Testing
16. Scalability and Resource Management
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.