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Joe Moura

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.

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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:

1. Role-playing: Assign specialized roles to agents

2. Memory: Provide agents with short-term, long-term, and shared memory

3. Tools: Assign pre-built and custom tools to each agent (e.g. for web search)

4. Focus: Break down the tasks, goals, and tools and assign to multiple AI agents for better performance

5. Guardrails: Effectively handle errors, hallucinations, and infinite loops

6. 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:

1. Tailor resumes and interview prep for job applications

2. Research, write and edit technical articles

3. Automate customer support inquiries

4. Conduct customer outreach campaigns

5. Plan and execute events

6. 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.

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What's inside

Syllabus

Multi AI Agent Systems with crewAI
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: 1. Role-playing: Assign specialized roles to agents 2. Memory: Provide agents with short-term, long-term, and shared memory 3. Tools: Assign pre-built and custom tools to each agent (e.g. for web search) 4. Focus: Break down the tasks, goals, and tools and assign to multiple AI agents for better performance 5. Guardrails: Effectively handle errors, hallucinations, and infinite loops 6. Cooperation: Perform tasks in series, in parallel, and hierarchicallyThroughout 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: 1. Tailor resumes and interview prep for job applications 2. Research, write and edit technical articles 3. Automate customer support inquiries 4. Conduct customer outreach campaigns 5. Plan and execute events6. 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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Designed for professionals with a background in business and AI, seeking to streamline workflows and enhance efficiency
Hands-on application of AI agents through the use of crewAI, an open-source library

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Multi AI Agent Systems with crewAI with these activities:
Review AI Principles
Refresh your knowledge of AI principles to strengthen your foundation for this course.
Browse courses on AI Principles
Show steps
  • Review notes or textbooks on AI principles
  • Complete practice questions or exercises on AI concepts
Brush up on probability and statistics
Review the basics of probability and statistics to strengthen your foundation for understanding AI agent systems.
Show steps
  • Review probability distributions and theorems
  • Practice solving statistical problems
Explore the crewAI library
Familiarize yourself with the crewAI library, which provides tools for building multi-agent systems, through available tutorials.
Show steps
  • Complete the introductory tutorial
  • Work through additional tutorials on specific agent capabilities
Eight other activities
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Show all 11 activities
Practice Solving Multi-Step AI Problems
Sharpen your problem-solving skills by practicing solving multi-step AI problems.
Show steps
  • Identify a multi-step AI problem
  • Develop a plan to solve each step in the problem
  • Implement your plan using crewAI
Participate in peer study sessions
Enhance your understanding through collaboration by engaging in study sessions with fellow learners to discuss concepts and work on assignments.
Show steps
  • Join or create a study group
  • Prepare for sessions by reviewing materials
  • Attend sessions and actively participate in discussions
Gather resources on multi-agent systems
Expand your knowledge by compiling a collection of resources on multi-agent systems, including articles, videos, and code samples.
Show steps
  • Conduct online research to find relevant materials
  • Organize the resources into categories or topics
Design and implement simple multi-agent systems
Reinforce your understanding of multi-agent systems by creating and implementing simple systems to perform specific tasks.
Show steps
  • Define the roles and responsibilities of each agent
  • Implement the communication and coordination mechanisms
  • Test and evaluate the performance of your system
Design a Multi-Agent System for a Business Process
Designing and implementing a multi-agent system for a specific business process will provide valuable hands-on experience and demonstrate your understanding of the course material.
Show steps
  • Identify a suitable business process to automate.
  • Design a multi-agent system architecture for the process.
  • Implement the system using CrewAI or other appropriate tools.
  • Test and evaluate the system's performance against specific metrics.
  • Document your design, implementation, and evaluation findings.
Build a multi-agent system for a real-world problem
Apply your knowledge to a real-world challenge by designing and implementing a multi-agent system to solve a specific problem.
Show steps
  • Identify a problem domain and define the goals
  • Design the multi-agent system architecture
  • Implement and test the system
Create a Multi-Agent System for a Business Process
Apply your learning by creating a multi-agent system to automate a business process of your choice.
Show steps
  • Identify a specific business process to automate
  • Break down the process into smaller tasks
  • Design and implement a multi-agent system using crewAI
  • Test and refine your system
Participate in AI competitions
Challenge yourself and test your skills by participating in AI competitions that focus on multi-agent systems.
Show steps
  • Identify relevant competitions
  • Prepare for the competition by practicing and refining your skills
  • Participate in the competition and showcase your abilities

Career center

Learners who complete Multi AI Agent Systems with crewAI will develop knowledge and skills that may be useful to these careers:

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