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Artificial Intelligence
Artificial Intelligence
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DeepLearning.AI 2

Multi AI Agent Systems with crewAI

  • up to 1 hour
  • Beginner

Exceed the performance of prompting a single LLM by designing and prompting a team of AI agents through natural language. Learn to automate repeatable, multi-step tasks and business processes using the open-source library, crewAI.

  • AI agent design
  • Role assignment
  • Memory management
  • Tool assignment
  • Task breakdown

Overview

In this course, you will learn key principles of designing effective AI agents and organizing a team of AI agents to perform complex, multi-step tasks. You will apply these concepts to automate six common business processes. By the end of the course, you will have designed several multi-agent systems to assist you in common business processes and studied the key principles of AI agent systems.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Professionals

Individuals looking to incorporate LLMs in their professional work.

Prompt Engineers

Those who have taken some prompt engineering courses and want to advance their skills.

Coders

People with basic coding familiarity who want to learn about AI agent systems.

Why should you take this course?

Artificial Intelligence

This course will teach you how to design and prompt a team of AI agents to perform complex tasks, enhancing your professional skills and automating business processes. Ideal for beginners and professionals looking to incorporate LLMs in their work.

Pre-Requisites

1 / 3

  • Familiarity with basic coding

  • Experience with prompt engineering

  • Interest in incorporating LLMs in professional work

What will you learn?

Introduction to AI Agent Systems
Learn the basics of AI agent systems and their applications.
Designing Effective AI Agents
Understand the principles of designing AI agents for specific roles and tasks.
Role-playing for AI Agents
Assign specialized roles to agents to enhance their performance.
Memory Management
Provide agents with short-term, long-term, and shared memory.
Tool Assignment
Assign pre-built and custom tools to each agent for specific tasks.
Task Breakdown and Assignment
Break down tasks, goals, and tools and assign them to multiple AI agents.
Error Handling
Effectively handle errors, hallucinations, and infinite loops in AI agents.
Cooperation Among AI Agents
Learn how agents can perform tasks in series, in parallel, and hierarchically.
Automating Business Processes
Apply AI agents to automate common business processes like resume tailoring and event planning.
Case Studies and Applications
Study real-world applications and case studies of multi-agent systems.

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