Working developers
You can code, but you want a clear, practical path to turning LLM capabilities into real workflows and applications you can ship.
AI Agents & Workflows - The Practical Guide
Learn how to programmatically build AI Workflows & Agents. All the theory, plenty of examples.
Course Overview
About This Course
You’ve probably heard “AI agents” everywhere—and it’s hard to tell what’s real, what’s hype, and what you can actually build. Maybe you’ve tried a few prompts, but turning that into something reliable that runs end-to-end still feels fuzzy.
This course strips away the buzzwords and shows you how agentic systems work in practice: the right amount of theory, lots of examples, and concrete code snippets so you understand how LLMs, regular code, and data fit together. You’ll see how to move from one-off outputs to repeatable systems you can adapt beyond a single language or model.
By the end, you’ll be able to create AI-powered applications that transform data, automate tasks, and coordinate multiple AI components. You’ll know when a workflow is enough, when an agent makes sense, and how to connect everything to real tools and services so it’s useful in day-to-day work.
What You'll Learn
A practical, code-driven guide to designing AI workflows and agentic systems with Python plus the OpenAI API & SDK, including tools, memory, integrations, and multi-agent coordination.
Design agents vs workflows
Explain what an AI workflow is versus an AI agent, how they relate, and how to choose the right approach for a given automation or application so you don’t over-engineer (or under-build).
Build from scratch
Create AI workflows and agents from the ground up, combining LLM calls with “normal code” and data so your systems behave predictably instead of feeling like a collection of prompts.
Use OpenAI programmatically
Call OpenAI models via the OpenAI API & SDK inside your own code, wiring model outputs into application logic so your AI features are part of a real system—not a demo.
Equip LLMs with tools
Add tool usage to your workflows (including web search) so the model can pull in external information and act on it, rather than relying only on what’s in the prompt.
Integrate third-party services
Connect your AI automations to external services like Slack, enabling workflows that can interact with the tools your team already uses instead of living in isolation.
Orchestrate multi-agent systems
Build multi-agent setups that share data, split work between universal and specialized agents, and incorporate both short- and long-term memory to keep behavior consistent across steps.
Ready to get started?
Prerequisites
Basic programming knowledge is required.
No advanced AI or programming experience is needed.
Who Is This Course For?
Automation builders
You’re tired of manual, repetitive tasks and want to replace them with AI-driven processes that actually run reliably end-to-end.
Agent-curious learners
You keep hearing about “AI agents,” but you want to understand what they really are, when they matter, and how to build them without getting lost in hype.
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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- Certificate of completion
- Hands-on exercises & projects
- Self-paced learning
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