Quick Guide & Tips

💻   Accessing Utils File and Helper Functions

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Open"

You will be able to see all the notebook files for the lesson, including any helper functions used in the notebook on the left sidebar. See the following image for the steps above.

🔄   Reset User Workspace

If you need to reset your workspace to its original state, follow these quick steps:

1:   Access the Menu: Look for the three-dot menu (⋮) in the top-right corner of the notebook toolbar.

2:   Restore Original Version: Click on "Restore Original Version" from the dropdown menu.

For more detailed instructions, please visit our Reset Workspace Guide.

💻   Downloading Notebooks

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Download as"

3:   Then, click on "Notebook (.ipynb)"

💻   Uploading Your Files

After following the steps shown in the previous section ("File" => "Open"), then click on "Upload" button to upload your files.

📗   See Your Progress

Once you enroll in this course—or any other short course on the DeepLearning.AI platform—and open it, you can click on 'My Learning' at the top right corner of the desktop view. There, you will be able to see all the short courses you have enrolled in and your progress in each one.

Additionally, your progress in each short course is displayed at the bottom-left corner of the learning page for each course (desktop view).

📱   Features to Use

🎞   Adjust Video Speed: Click on the gear icon (⚙) on the video and then from the Speed option, choose your desired video speed.

🗣   Captions (English and Spanish): Click on the gear icon (⚙) on the video and then from the Captions option, choose to see the captions either in English or Spanish.

🔅   Video Quality: If you do not have access to high-speed internet, click on the gear icon (⚙) on the video and then from Quality, choose the quality that works the best for your Internet speed.

🖥   Picture in Picture (PiP): This feature allows you to continue watching the video when you switch to another browser tab or window. Click on the small rectangle shape on the video to go to PiP mode.

√   Hide and Unhide Lesson Navigation Menu: If you do not have a large screen, you may click on the small hamburger icon beside the title of the course to hide the left-side navigation menu. You can then unhide it by clicking on the same icon again.

🧑   Efficient Learning Tips

The following tips can help you have an efficient learning experience with this short course and other courses.

🧑   Create a Dedicated Study Space: Establish a quiet, organized workspace free from distractions. A dedicated learning environment can significantly improve concentration and overall learning efficiency.

📅   Develop a Consistent Learning Schedule: Consistency is key to learning. Set out specific times in your day for study and make it a routine. Consistent study times help build a habit and improve information retention.

Tip: Set a recurring event and reminder in your calendar, with clear action items, to get regular notifications about your study plans and goals.

☕   Take Regular Breaks: Include short breaks in your study sessions. The Pomodoro Technique, which involves studying for 25 minutes followed by a 5-minute break, can be particularly effective.

💬   Engage with the Community: Participate in forums, discussions, and group activities. Engaging with peers can provide additional insights, create a sense of community, and make learning more enjoyable.

✍   Practice Active Learning: Don't just read or run notebooks or watch the material. Engage actively by taking notes, summarizing what you learn, teaching the concept to someone else, or applying the knowledge in your practical projects.

📚   Enroll in Other Short Courses

Keep learning by enrolling in other short courses. We add new short courses regularly. Visit DeepLearning.AI Short Courses page to see our latest courses and begin learning new topics. 👇

👉👉 🔗 DeepLearning.AI – All Short Courses [+]

🙂   Let Us Know What You Think

Your feedback helps us know what you liked and didn't like about the course. We read all your feedback and use them to improve this course and future courses. Please submit your feedback by clicking on "Course Feedback" option at the bottom of the lessons list menu (desktop view).

Also, you are more than welcome to join our community 👉👉 🔗 DeepLearning.AI Forum

Sign in

Or, sign in with your email
Email
Password
Forgot password?
Don't have an account? Create account
By signing up, you agree to our Terms Of Use and Privacy Policy

Create Your Account

Or, sign up with your email
Email Address

Already have an account? Sign in here!

By signing up, you agree to our Terms Of Use and Privacy Policy

Choose Your Plan

MonthlyYearly

Change Your Plan

Your subscription plan will change at the end of your current billing period. You’ll continue to have access to your current plan until then.

Learn More

Welcome back!

Hi ,

We'd like to know you better so we can create more relevant courses. What do you do for work?

DeepLearning.AI
CourseBeginner3 hours 45 mins

Design, Develop, and Deploy Multi-Agent Systems with CrewAI

Instructor: João Moura

CrewAI logo
  • Beginner
  • 3 hours 45 mins
  • 38 Video Lessons
  • 6 Code Examples
  • Instructor: João Moura
    • CrewAI
    CrewAI

Your path to production-ready agents

  • Build agentic systems that work together: Create multi-agent workflows where agents plan, reason, and collaborate to complete complex tasks reliably, including with tool use and MCP servers

  • Control and improve your agents: Use memory, guardrails, execution hooks, traces, and low-level control layers to ensure reliable, repeatable outcomes.

  • Deploy with confidence: Orchestrate agents with two common paradigms – Crews and Flows – that allow you to scale systems from prototype to production.

Why Enroll

AI agents leverage the power of Large Language Models (LLMs), but, as with all LLM-based tools, they struggle with reliability, coordination, and repeatability when deployed on complex workflows. AI agents build on these models to move from responding to prompts to acting autonomously, reasoning through tasks, and adapting to changing goals. Multi-agent systems extend this capability even further by distributing reasoning and responsibilities across specialized agents that can plan, collaborate, and improve together.

While it’s never been faster to prototype a concept, many teams are still stuck at this prototype stage, where agents might run well at a small scale but fail under real-world conditions. In this course, you’ll bridge that gap by turning prototypes like an automated code reviewer, a meeting co-pilot, and a deep researcher into production-ready systems. You’ll use the CrewAI framework to apply methods that improve control, reliability, and scalability.

Across four modules, you’ll:

  • Build AI agents using core the building blocks of memory, tools (including MCP servers), guardrails, and execution hooks.
  • Design and orchestrate multi-agent workflows using Flows and complex coordination strategies. In hands-on labs, create and refine crews for projects such as a deep researcher and a meeting co-pilot.
  • Add observability and evaluation through traces, testing with LLM-as-a-Judge techniques, and training with human feedback to monitor agent decisions, debug issues, and continuously improve performance.
  • Deploy and monitor agents safely in production, integrating zoom-in and zoom-out observability metrics, versioning your configurations, and scaling reliably with production-grade practices.

By the end, you’ll know how to turn your agent ideas into scalable systems that are robust, observable, and ready for real-world use.

In partnership with

null

We built this course with the CrewAI team to share the framework and techniques powering many of today’s most advanced agentic systems. You’ll learn directly from João Moura, Co-founder and CEO of CrewAI, through hands-on labs that guide you from building single agents to deploying multi-agent systems ready for production.

Who should join?

This course is designed for AI builders and technical professionals who want to understand, build, and scale AI agent systems, from engineers and developers to students and technical leaders guiding AI adoption. Whether you’re hands-on with code or leading development teams, you’ll gain the knowledge to design multi-agent workflows, integrate them into real applications, and make informed decisions about deploying them safely and reliably.

Instructor

João Moura

João Moura

Founder and CEO of CrewAI

Course Outline

Design, Develop, and Deploy Multi-Agent Systems with CrewAI

Module 1: Foundations of AI Agents
Module 2: Working with AI Agents
Module 3: Managing Systems of AI Agents
Module 4: Applying AI Agents in Business

You’ll earn a certificate upon completing the course, recognizing your skills in designing, developing, and deploying multi-agent systems!

What Learners From Previous Courses Say About DeepLearning.AI

Jan Zawadzki

“Within a few minutes and a couple slides, I had the feeling that I could learn any concept. I felt like a superhero after this course. I didn’t know much about deep learning before, but I felt like I gained a strong foothold afterward.”

Kritika Jalan

“The whole specialization was like a one-stop-shop for me to decode neural networks and understand the math and logic behind every variation of it. I can say neural networks are less of a black box for a lot of us after taking the course.”

Chris Morrow – Deep Learning Specialization

“During my Amazon interview, I was able to describe, in detail, how a prediction model works, how to select the data, how to train the model, and the use cases in which this model could add value to the customer.”

Learner Reviews

Frequently Asked Questions

I already have Python experience, is this course for me?

Yes! This course is perfect for anyone with a background in Python ready to dive deeper into agentic AI and multi-agent systems!

I have questions about my DeepLearning.AI Pro subscription, whom can I ask?
How much does a Pro membership cost?

The DeepLearning.AI Pro membership costs $25/mo billed annually and $30/mo billed monthly.

More pricing details are available on the membership page.

Important details:

  • All prices are listed in USD
  • Payments are processed securely via Stripe
  • Taxes may apply depending on your location
Will I receive a certificate at the end of the course?

Yes! You’ll earn a certificate upon completing the course, recognizing your skills in building and deploying multi-agent systems.

Join today and be on the forefront of the next generation of AI!

Want to learn more about Generative AI?

Keep learning with updates on curated AI news, courses, events, as well as Andrew’s thoughts from DeepLearning.AI!