Deep Learning A-Z 2026: Mạng Nơ-ron, AI & Giải thưởng ChatGPT
Kirill Eremenko
AI Agents & Workflows - The Practical Guide
"AI Agents" is a buzzword.
That's a pity, because AI powered workflows and agentic systems can unlock an entire new world of opportunities.
From data transformation to content generation, customer service or automated research. Your imagination is the limit!
And this course will get you there: You'll be able to build your own AI-powered applications and agentic systems!
This course will teach you what exactly "AI Agents" are, how they differ from (and still relate to) "AI Workflows" and how you can build and use both.
With this course, I decided to take a step back from the buzzwords and instead give you all the crucial theory, plenty of examples and concrete code snippets to ensure that you fully understand how LLMs, "normal code" and data work together to bring AI-powered applications to life.
With this course, you'll get:
A thorough explanation of "AI Workflows" & "AI Agents"
Lots of examples (incl. content generation, customer support, automated research)
Detailed explanations that allow you to apply the knowledge no matter which programming language you're using
You'll learn:
How to build AI Workflows & Agents from scratch
How to use OpenAI's models (via API & SDK) programmatically
How to transform input data with AI
How to build AI-powered automations
How to interact with third-party services like Slack
How use AI for self-evaluation
How to manage short- and long-term memory for your AI Agents
How to build Multi-Agent systems and share data between agents
How to split work between universal and specialized Agents
How to add a Human-in-the-Loop step to your workflows
And so much more!
All code examples in this course use Python and the OpenAI API / SDK but you'll be able to apply the knowledge to any programming language or model you're using in your day-to-day work.
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