Buenísima forma de entender cómo varios agentes pueden colaborar en vez de trabajar uno solo con AutoGen. Me gustó especialmente el ejemplo donde un agente revisa el trabajo de otro antes de dar la respuesta final, se siente mucho más cercano a un flujo de trabajo real.
Building Multi-Agent Systems with AutoGen and Python
Start building collaborative AI workflows and conversational agents using the AutoGen framework in Python.
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AI instructor
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About this course
AI is moving beyond single-prompt interactions into collaborative ecosystems where multiple agents work together. If you want to orchestrate intelligent AI conversations, the AutoGen framework is a powerful starting point.
In this text-based course, you will learn how to design, configure, and manage multi-agent systems in Python. You will start with foundational AI concepts and terminology, then progress to writing code for custom agents that can communicate, execute tasks, and retrieve information to solve problems autonomously.
What you'll learn:
• Understand the foundational concepts of multi-agent systems and AI orchestration.
• Configure your Python environment using modern packaging tools and virtual environments.
• Build and customize conversational agents using the AutoGen framework.
• Implement Retrieval-Augmented Generation (RAG) patterns to give agents external knowledge.
• Apply prompt engineering basics to guide agent behavior and collaboration.
• Practice coordinating complex workflows through written code exercises.
The course flows logically from essential definitions and basic agent setup to more advanced collaborative patterns. You will read through clear explanations, study practical Python snippets, and reinforce your skills through structured written exercises.
This course is designed for beginners and Python developers looking to explore agentic AI without needing prior machine learning expertise.
Start reading today to build your first team of collaborative AI agents.
What you'll get
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Certificate of completion
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Audio version included
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Short & focused
3h of practical content
Reviews (8)
একাধিক এজেন্টকে একসাথে কথা বলিয়ে কাজ করানোর ব্যাপারটা আগে খুব জটিল লাগত, কিন্তু AutoGen দিয়ে এটা কত সহজ তা এই কোর্স দেখিয়ে দিল। কথোপকথনমূলক এজেন্ট কীভাবে নিজেদের মধ্যে বার্তা আদান-প্রদান করে আর একটা সমস্যা সমাধানে সহযোগিতা করে, সেটা পরিষ্কারভাবে বোঝানো হয়েছে। পাইথনের উদাহরণগুলো হুবহু চলে, কোনো ঝামেলা ছাড়াই আমার নিজের একটা ছোট দল বানিয়ে ফেলেছি। বিশেষ করে এজেন্টদের ভূমিকা ঠিক করার অংশটা দারুণ কাজে লেগেছে। শুরু করার জন্য এর চেয়ে ভালো গাইড পাওয়া কঠিন।
Je cherchais à comprendre comment faire dialoguer plusieurs agents, et AutoGen est devenu limpide grâce à ce cours. La construction des agents conversationnels en Python est très bien décortiquée, avec des exemples qui tournent du premier coup. J'ai pu monter un petit flux collaboratif en une soirée.
Konsep multi-agent yang biasanya terasa abstrak jadi masuk akal setelah lihat contoh nyata pakai AutoGen di kursus ini. Bagian yang paling saya suka adalah saat beberapa agent saling berdiskusi dan mengoreksi jawaban satu sama lain sebelum hasil akhir diberikan, itu terasa seperti melihat tim kerja beneran.
Bonne intro à AutoGen, un peu dense par moments.
Cara menjelaskan bagaimana agent-agent AutoGen saling berkomunikasi untuk menyelesaikan tugas benar-benar membuka wawasan baru buat saya.
شرح جيد لبناء أنظمة متعددة الوكلاء باستخدام AutoGen.
I went in expecting a basic intro to chatbots and came out with a real understanding of how conversational agents can collaborate to solve tasks neither could handle alone. The course walks through setting up AutoGen from scratch, then gradually adds agents with different roles so you can watch them debate and refine an answer together. What stood out most was the section on giving agents tools to call and letting them negotiate who handles which subtask, which is something I hadn't seen explained this clearly before. The pacing lets you actually run the code alongside the instructor instead of just watching a demo. By the last module I had a working multi-agent pipeline that could research, critique, and rewrite its own output.
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Frequently asked
What do I need to take this course? +
Just a phone or computer with internet. No installs, no special hardware.
How do I pay? +
By card via Stripe. We don’t store card details — Stripe handles them securely.
Can I get a refund? +
Yes — full refund within 14 days, no questions asked.
How long will I have access? +
Forever. Once you purchase, the course is yours to revisit anytime.
Will I get a certificate? +
Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.
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