Intro · 1:17
Course structure
A condensed version of an 8-hour course.
- Notes from Andrew Ng's agentic AI course.
- Five modules.
- Saves hours.
| Module | Topic |
|---|---|
| 1 | Fundamentals |
| 2 | Reflection |
| 3 | Tool use |
| 4 | Evals |
| 5 | Autonomy |
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Whose course?
Andrew Ng's.
How many modules?
Five.
0:00 A portion of this video is sponsored by HubSpot Media. Let's first go over the structure of the course. The Agentic AI course has five modules. Module one, introduction to Agentic Workflows, covers the foundations of Agentic AI and is what the rest of the course is built on top of. Module two is a deep dive into the reflection pattern, a common pattern for agentic workflows. Module three covers tool use, another common agentic pattern. The course also covers lots of examples and ways to improve the results.
0:48 Module four is called practical tips for building agentic AI. And this module is by far the most important module. I have not seen this information especially on evaluations being covered to this depth anywhere else. It's what everybody talks about but nobody has actually really covered it well and this course does it well. And finally module five is patterns for highly autonomous agents where Andrew covers more experimental agentic workflows a taste for the future. All right let's jump into module one the fundamentals starting off by defining agentic AI.
1:10 An agentic AI workflow is defined as a process where an LLM based app executes multiple steps to complete a task. For example, if you want your agentic AI workflow to help you write an
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