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Free AI Agents Course: Build Autonomous AI Workflows

Master AI agents from first principles with no code required. This free course demystifies agent anatomy, the observe-think-act loop, and core concepts like RAG, tool use, and multi-agent systems. Build real agents using n8n...

10 lessons 16h 19min total Free

Course overview

This course provides a structured path from understanding what AI agents are to building and deploying them. It clarifies the difference between generative AI, agentic AI, and autonomous agents. You will learn the fundamental agent anatomy including the brain, memory, and tools, along with design patterns like reflection, planning, and the observe-think-act loop. The curriculum covers practical implementation with no-code platforms like n8n and coding frameworks like LangChain, integrating APIs, webhooks, and the Model Context Protocol. You'll explore advanced concepts such as Retrieval-Augmented Generation, multi-agent orchestration, state management, and deploying production-ready automations, moving well beyond the capabilities of a standard chatbot.

Who this course is for

This course is designed for absolute beginners, entrepreneurs, and developers who want to leverage AI agents without prior programming experience. It is ideal for those seeking to automate complex business workflows, build custom AI solutions, or explore the commercial potential of agent deployment. If you understand the value of automation but feel blocked by technical jargon, this sequence of lessons provides a straightforward entry point using no-code tools like n8n. For those with some python experience, dedicated sections cover building agents from scratch using LangChain and Claude's API to create custom, structured solutions.

How to study this sequence

Begin with the fundamentals by watching the first lessons to ground yourself in what distinguishes an agent from a simple automation or chatbot. The course is sequenced to introduce core theory before diving into practice. Start with the no-code n8n tutorials to build your first working agent immediately, gaining tangible confidence. Then, progress to the more in-depth Python and LangChain sections to understand programmatic control. Refer to the comparative lessons on generative AI versus agentic AI whenever you need clarity on how these systems relate. For the deepest learning, actively code along with the demonstrations to encounter and resolve real-world implementation challenges.

What you should be able to do

By completing this course, you will have built multiple functional AI agents using both no-code and code-based approaches. You will be able to articulate the architecture of an agent, design a system prompt, connect tools like APIs and Google Sheets, and implement a RAG pipeline. You will move from a theoretical understanding to practical skill, capable of selecting the right platform, debugging workflows, and architecting simple multi-agent systems. The final result is a portfolio of autonomous workflows that demonstrates your ability to design solutions for real-time adaptation and multi-step problem solving.

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What you learn in this AI Agents course

This course organizes 10 AI Agents lessons in a practical order, starting with the base and moving toward examples you can repeat in your own projects.

The main practice points are Understand the core definition and mechanics of AI agents versus traditional automations, Master the three essential components: brain, memory, and tools, Build a working AI agent using n8n without writing any code and Implement API integrations and HTTP requests in agent workflows. Use this page to review the course proposal, check the key topics, and open the lessons in the recommended order.

What you will practice

  • Understand the core definition and mechanics of AI agents versus traditional automations
  • Master the three essential components: brain, memory, and tools
  • Build a working AI agent using n8n without writing any code
  • Implement API integrations and HTTP requests in agent workflows
  • Set up guardrails and safety mechanisms for responsible agent deployment
  • Test, debug, and expand agent capabilities for real-world applications

Concepts covered

AI Agents Language Models Memory Systems API Integration Guardrails Automation vs. Agents HTTP Requests Agent Tools

Course lessons

10 tutoriais organizados em sequência.

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Course summary

This AI Agents course brings together 10 lessons in a guided sequence. It starts with "From Zero to Your First AI Agent in 25 Minutes (No Coding)" and moves step by step, so each lesson supports the next one and helps turn the topic into practice.

During the course, the practical focus is on Understand the core definition and mechanics of AI agents versus traditional automations, Master the three essential components: brain, memory, and tools, Build a working AI agent using n8n without writing any code and Implement API integrations and HTTP requests in agent workflows. These points help you watch with a goal instead of treating the lesson as a loose introduction.

The course also introduces important ideas such as AI Agents, Language Models, Memory Systems, API Integration and Guardrails, which makes it easier to understand later tutorials and decide when each resource is useful.

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How to get more from this course

Who this AI Agents course is for

This advanced course is for learners who already understand the fundamentals of AI Agents and want to develop deeper technical or professional skills.

What you can do after finishing

By the end, you should be able to review the main idea of the course and practice Understand the core definition and mechanics of AI agents versus traditional automations, Master the three essential components: brain, memory, and tools, Build a working AI agent using n8n without writing any code and Implement API integrations and HTTP requests in agent workflows with more confidence.

Recommended study order

Watch the 10 lessons in the order shown on this page. Pause after each lesson to repeat the examples and only move on when the previous step makes sense.

What to study next

After finishing the course, explore the AI Agents topic to find related tutorials and keep studying with more context.

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Course questions

Is this AI Agents course for beginners?

No. This course covers advanced AI Agents topics and is best suited to learners who already understand the fundamentals.

How many lessons are in this course?

This course currently has 10 lessons and about 16h 19min in total.

What should I do after finishing the course?

The best next step is to explore the AI Agents topic and choose a related tutorial that matches what you want to practice.

Is this course free?

Yes. This is a free course organized by CursoB so you can study AI Agents in a structured sequence.

Do I need previous experience to follow the course?

Yes. You should already understand the fundamentals of AI Agents before starting this advanced course.

Should I watch the lessons in order?

Yes. The recommended path is to watch the 10 lessons in the order shown, because each lesson helps prepare the next one.

Can I use this course for practical projects?

Yes. Use the course as a practical reference to train Understand the core definition and mechanics of AI agents versus traditional automations, Master the three essential components: brain, memory, and tools, Build a working AI agent using n8n without writing any code and Implement API integrations and HTTP requests in agent workflows and adapt the examples to your own projects.

Does this course include a certificate?

CursoB stopped issuing certificates for its own courses in May 2026. CursoB no longer offers completion certificates. Courses and tutorials remain free to study. If content is hosted on another platform, any certificate depends exclusively on the original author or platform rules.

Are the lessons updated?

CursoB periodically reviews the AI Agents catalog and may add, remove, or reorder lessons when better content is found.

Where can I find more content on this subject?

Explore the AI Agents topic to find related tutorials and complementary courses.

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What each course lesson covers

Use these notes to understand the sequence before opening each lesson.

  1. 01 From Zero to Your First AI Agent in 25 Minutes (No Coding) In this lesson, you practice Understand the core definition and mechanics of AI agents versus traditional automations, Master the three essential components: brain, memory, and tools and Build a working AI agent using n8n without writing any code.
  2. 02 How to Build & Sell AI Agents: Ultimate Beginner’s Guide In this lesson, you practice Understand the core anatomy and components that make AI agents function effectively, Build functional AI agents using no-code platforms across multiple use cases and Design and structure tools, APIs, and schemas for agent decision-making.
  3. 03 Build & Sell n8n AI Agents (8+ Hour Course, No Code) In this lesson, you practice Build and deploy AI agents without writing code using n8n, Design RAG pipelines, customer support workflows, and content creation automations and Integrate external APIs and services to extend agent capabilities.
  4. 04 AI Agents Fundamentals In 21 Minutes In this lesson, you practice Understand the definition and core capabilities that distinguish AI agents from standard language models, Learn agentic design patterns including reflection, tool-use, and planning approaches and Apply multi-agent systems and coordination mechanisms for complex collaborative tasks.
  5. 05 Build an AI Agent From Scratch in Python – Tutorial for Beginners In this lesson, you practice Build an AI agent from scratch using Python and LangChain framework, Integrate language models like Claude and GPT into your applications and Create structured outputs using Pydantic models and output parsing.
  6. 06 Don’t learn AI Agents without Learning these Fundamentals In this lesson, you practice Understand how LLMs work internally and why tokens and context windows matter, Apply embeddings and vector representations to build semantic search systems and Build production-ready AI applications with LangChain framework.
  7. 07 Building AI Agents that actually work (Full Course) In this lesson, you practice Understand the observe-think-act loop that powers all AI agent platforms, Implement context engineering using agents.md and memory.md files for persistent, improving agents and Connect external tools like Gmail, Calendar, and Stripe via Model Context Protocol.
  8. 08 Generative AI Vs Agentic AI Vs AI Agents In this lesson, you practice Understand the core differences between generative AI, agentic AI, and AI agents, Learn how agentic AI systems adapt in real-time and solve multi-step problems and Identify practical applications of each AI category in business and research.
  9. 09 The AI Agent Tutorial That Should’ve Been Your First (no code) In this lesson, you practice Build a functional AI agent without coding using n8n, Configure an agent's brain with language models and system prompts and Connect external tools like Google Sheets to enable agent actions.
  10. 10 Generative AI vs AI agents vs Agentic AI In this lesson, you practice Distinguish between generative AI, AI agents, and agentic AI systems, Understand how agentic systems combine reasoning with autonomous action and Recognize appropriate use cases for each AI paradigm.