AI users and knowledge workers
You use tools such as ChatGPT or Claude and want to understand what agent capabilities add, where their limits are, and how to work with them productively.
AI Agents & Workflows - The Practical Guide
Understand how modern AI agents and workflows really work—and learn to use or build them with visual tools, Python, and leading frameworks.
Course Overview
About This Course
“AI agent” has become a buzzword—but real agents and AI-powered workflows can unlock a huge range of practical opportunities. They can summarize documents, generate files, support customers, research topics, and connect to tools such as Slack.
This course cuts through the hype and gives you a clear, practical mental model of what agents are, how they work behind the scenes, and how they differ from AI workflows. You’ll explore them both as a user of tools such as Claude Cowork and ChatGPT-style agents and as a builder who wants to plan or create agents visually or in code.
This is not primarily a programming course. Visual n8n projects, step-by-step Python examples, and framework-based builds make the concepts concrete without tying them to one stack. By the end, you’ll understand the moving parts, know when a simple workflow is the better choice, and be ready to use agents productively or design your own.
What You'll Learn
Build a practical, transferable understanding of modern AI agents and workflows—from the agent loop and tool use to visual n8n builds, Python examples, safety controls, and agent frameworks.
Agents vs workflows
Understand what AI agents and AI workflows really are, how they differ, and when a predictable workflow is a better choice than an autonomous agent.
Master the agent anatomy
Explore models, harnesses, the agent loop, tools, instructions, context and sessions, skills, memory, sandboxes, and humans-in-the-loop as the core building blocks of modern agents.
Build visually and in code
Create practical AI workflows and agents with n8n, then follow step-by-step Python implementations to see how the same ideas translate into code.
Understand tool use
Learn how LLMs use tools, compare primitive and provider-native tool calling, and build agents that can summarize text, create PDFs, work with files, and run commands.
Control context and safety
Steer agents with system instructions, AGENTS.md, CLAUDE.md, and skills; manage context, sessions, compaction, and memory; and constrain risky actions with sandboxes and human approval.
Use frameworks and integrations
See how frameworks such as Eve and CrewAI accelerate agent development, survey options including Vercel AI SDK, LangGraph, and Pydantic AI, and expose task-specific agents through integrations such as Slack.
Ready to get started?
See enrollment optionsPrerequisites
No prior AI-agent or advanced AI knowledge is required.
You do not need to be a developer—the visual projects and code examples are explained step by step.
Basic programming knowledge is helpful if you want to follow and adapt the Python examples.
Who Is This Course For?
Automation and no-code builders
You want to design useful AI workflows and agents visually, connect them to real tools, and choose the right level of autonomy for each task.
Developers and technical builders
You want a stack-independent mental model plus practical Python and framework examples you can transfer to your preferred language, model, or platform.
Curriculum Overview
Start NowPreview the structure and pacing of this course before you begin.
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AI Agents & Workflows - The Practical Guide
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