What you'll learn

Exceed the performance of prompting a single LLM by designing and prompting a team of AI agents through natural language.
Use an open source library, crewAI, to automate repeatable, multi-step tasks like tailoring a resume to a job description; and automate business processes that are typically done by a group of people, like event planning.
By creating a team of AI agents, you can define a specific role, goal, and backstory for each agent, which breaks down complex multi-step tasks and assigns them to agents that are customized to perform those tasks.

Course recap

PRO

This course teaches how to build multi-agent systems using CrewAI, a framework for orchestrating role-playing AI agents that collaborate on complex tasks. With 18 lessons, it covers agent definition with roles and goals, task assignment, tool integration, and crew orchestration patterns for real-world use cases including research, writing, customer support, financial analysis, and event planning.

Concept map

Key concepts

AI AgentsRole-playing AI agents with defined roles, goals, backstories, and tool access that collaborate within crews
Tool CallingTools as the translation layer allowing agents to interact with APIs, databases, and external systems; must be versatile, fault-tolerant, and cached
Multi agent orchestrationPatterns for coordinating multiple specialized agents on complex tasks through sequential and hierarchical workflows

About this course

Learn key principles of designing effective AI agents, and organizing a team of AI agents to perform complex, multi-step tasks. Apply these concepts to automate 6 common business processes.

Learn from João Moura, founder and CEO of crewAI, and explore key components of multi-agent systems:

Role-playing: Assign specialized roles to agents
Memory: Provide agents with short-term, long-term, and shared memory
Tools: Assign pre-built and custom tools to each agent (e.g. for web search)
Focus: Break down the tasks, goals, and tools and assign to multiple AI agents for better performance
Guardrails: Effectively handle errors, hallucinations, and infinite loops
Cooperation: Perform tasks in series, in parallel, and hierarchically

Throughout the course, you’ll work with crewAI, an open source library designed for building multi-agent systems. You’ll learn to build agent crews that execute common business processes, such as:

Tailor resumes and interview prep for job applications
Research, write and edit technical articles
Automate customer support inquiries
Conduct customer outreach campaigns
Plan and execute events
Perform financial analysis

By the end of the course, you will have designed several multi-agent systems to assist you in common business processes, and also studied the key principles of AI agent systems.

Who should join?

If you’ve taken some prompt engineering courses, have some familiarity with basic coding, and want to incorporate LLMs in your professional work, then this course is designed for you!