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Building Multi-Agent Systems (Hands-On)
New
Rating: 5.0 out of 5(6 ratings)
669 students

Building Multi-Agent Systems (Hands-On)

Master Multi-Agent AI Systems, Agent Communication, and Real-World Automation Techniques
New
Created byYotta Academy
Last updated 5/2026
English

What you'll learn

  • Understand the fundamentals of Multi-Agent Systems and how autonomous agents communicate, collaborate, and coordinate tasks.
  • Build practical AI agents from scratch and design systems where multiple agents work together to solve complex problems.
  • Implement agent communication and orchestration using modern frameworks and tools used in real-world AI applications.
  • Design and deploy collaborative AI workflows where agents handle tasks such as planning, reasoning, and decision-making.
  • Create real-world projects using multi-agent architectures, including task automation, research assistants, and intelligent workflows.

Course content

5 sections • 24 lectures • 43m total length

  • From Chatbot to Agent1:53
  • The React Loop (Think, Act, Observe)1:51
  • Hands-on Setup0:56
  • DEMO - Setup - CrewAI2:51

Requirements

  • 1. Basic understanding of Python programming
  • 2. Familiarity with AI concepts or Large Language Models (LLMs) is helpful but not required
  • 3. A computer with internet access (Windows, macOS, or Linux)
  • 4. Basic knowledge of APIs and Python packages is a plus but not mandatory

Description

This course contains the use of artificial intelligence. AI tools are used to generate video for better quality.
This course primarly taught about Crew-AI Agents and how it works. Please note that all demos and evaluations are performed using a manually.

Building Multi-Agent Systems (Hands-On) is a practical course designed to help you understand and build powerful AI systems where multiple intelligent agents collaborate to solve complex tasks.

Modern AI applications are rapidly moving toward multi-agent architectures, where different AI agents work together, communicate, plan, and execute tasks more efficiently than a single model. In this course, you will learn how these systems work and how to build them from scratch through hands-on projects.

We will start by exploring the fundamentals of AI agents and multi-agent systems, including how agents communicate, coordinate, and share information. From there, you will dive into practical implementation where you will design and develop systems where multiple agents collaborate to complete real-world tasks.

Throughout the course, you will build real projects such as task automation systems, AI research assistants, and intelligent workflows. You will also learn how to structure agent roles, manage communication between agents, and design scalable agent architectures.

By the end of this course, you will have the skills needed to design, build, and deploy your own multi-agent AI systems. Whether you are a developer, AI enthusiast, or software engineer, this course will give you practical knowledge that you can apply to real-world AI applications.

If you want to stay ahead in the rapidly evolving world of AI and learn how to build collaborative intelligent systems, this course will provide the tools and hands-on experience you need.

Who this course is for:

  • Python programmers interested in AI automation and intelligent systems
  • Students and professionals curious about next-generation AI architectures
  • AI enthusiasts who want hands-on experience building multi-agent workflows

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