This course offers a comprehensive overview of understanding and designing AI agent systems powered by large language models (LLMs). You’ll explore core AI agent components, delve into diverse architectural patterns, discuss critical safety measures, and examine real-world AI applications. You’ll learn to deal with associated challenges in agentic system design.
You will study real-world examples, including the Multi-Agent Conversational Recommender System (MACRS), NVIDIA’s Eureka for reward generation, and advanced agents navigating live websites and creating complex images. Drawing on insights from industry deployments and cutting-edge research, you will gain the foundational knowledge to confidently start designing your agent-based systems. This course is ideal for anyone looking to build smarter and more adaptive AI systems powered by LLMs.
This course offers a comprehensive overview of understanding and designing AI agent systems powered by large language models (LL...Show More
WHAT YOU'LL LEARN
An understanding of AI agents and how they differ from AI models
The ability to identify and explain core AI agent components and memory systems
An explanation of different agent orchestration patterns and how to choose among them
Hands-on experience designing and implementing AI agent safety guardrails
Knowledge of integrating human oversight into agent workflows
Understanding and applying strategies to overcome challenges in agentic systems
Hands-on experience deconstructing real-world AI agent case studies
Understanding the design and architecture of adaptive and robust AI agent systems
An understanding of AI agents and how they differ from AI models
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Content
1.
Agent Design Fundamentals
6 Lessons
Learn core AI agent components, architecture, and how they perceive, reason, and act. Master orchestration, safety, and key design challenges.
2.
Multi-Agent Conversational Recommender System (MACRS)
4 Lessons
Explore MACRS, a multi-agent system for goal-directed conversational recommendations. See how it plans, uses reflection, and achieves superior performance.
3.
Nvidia Eureka Learning Agent
6 Lessons
Dive into Eureka, an LLM-powered agent that autonomously designs and refines RL reward functions. Learn about its evolutionary search and human feedback integra
4.
Applying Agentic Design Principles
1 Lessons
5.
Designing an AI Agent for Generating LLM Pipelines
4 Lessons
Explore ChainBuddy’s innovative solutions for efficient LLM evaluation and workflow generation.
6.
Designing a Web Agent
5 Lessons
Explore the development of advanced multimodal web agents for enhanced task performance.
7.
Designing a Multimodal-LLM Agent for Multi-Object Diffusion
4 Lessons
Explore MuLan's innovative approach to enhancing text-to-image generation through interactive, multi-step processes.
8.
Thought Exercise: AI Hospital
1 Lessons
Design a self-improving multi-agent system for enhanced medical diagnosis.
9.
Wrapping up
1 Lessons
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
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