Agentic System Design

Learn to design the next generation of AI systems. Explore the architectures and strategies behind autonomous agents that solve complex, real-world problems.

Advanced

33 Lessons

Certificate of Completion

Learn to design the next generation of AI systems. Explore the architectures and strategies behind autonomous agents that solve complex, real-world problems.

AI-POWERED

Code Feedback

Explanations

AI-POWERED

Code Feedback

Explanations

This course includes

19 AI Feedbacks

5 Quizzes

This course includes

19 AI Feedbacks

5 Quizzes

Course Overview

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, an...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

What You'll Learn

An understanding of AI agents and how they differ from AI models

Course Content

Agent Design Fundamentals

Learn core AI agent components, architecture, and how they perceive, reason, and act. Master orchestration, safety, and key design challenges.

Introduction to AI Agents

Agent Architecture: Core Agent Components Agent Architecture: Components Interaction and Agent Memory Structuring Agent Behavior: Agent Orchestration Patterns Building Trustworthy Agents: Guardrails and Human Oversight Key Challenges and Design Strategies in Agentic AI Systems

Multi-Agent Conversational Recommender System (MACRS)

Explore MACRS, a multi-agent system for goal-directed conversational recommendations. See how it plans, uses reflection, and achieves superior performance.

Introduction to MACRS and the Design Challenge MACRS Multi-Agent Act Planning Framework MACRS User Feedback-Aware Reflection Mechanism Evaluating MACRS: Performance and Insights

Nvidia Eureka Learning Agent

Dive into Eureka, an LLM-powered agent that autonomously designs and refines RL reward functions. Learn about its evolutionary search and human feedback integra

Eureka: Automating Reward Design with Coding LLMs Eureka’s Zero-Shot Reward Generation Eureka’s Evolutionary Search for Iterative Improvement Eureka's Reward Reflection Mechanism Eureka from Human Feedback and Novel Reward Discovery Evaluating Eureka: Performance and Insights

Applying Agentic Design Principles

Thought Exercise: Design a Smart Parking Agent System

Designing an AI Agent for Generating LLM Pipelines

Explore ChainBuddy’s innovative solutions for efficient LLM evaluation and workflow generation.

Introduction to ChainBuddy and the “Blank Page Problem”The Requirement-Gathering Chat Assistant The Multi-Agent Pipeline Generation Framework Evaluating ChainBuddy: Performance, Usability, and Design Insight

Designing a Web Agent

5 Lessons

Explore the development of advanced multimodal web agents for enhanced task performance.

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.

Thought Exercise: AI Hospital

1 Lesson

Design a self-improving multi-agent system for enhanced medical diagnosis.

Wrapping up

1 Lesson

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