131 minutesHow I use LLMs
You can recognize when to follow up, when to switch models and when to start a fresh conversation, calibrated against real day-to-day usage.
Tina Huang. A condensed run through Google's prompt engineering course covering frameworks for clarity, iteration methods, and worked examples for emails, summaries, and analysis. Useful if you want a second pass that maps the same structural ideas onto the kinds of tasks you actually hit during a workday.
Watch it for breadth after the primary pick's depth; its value here is mapping the same structure onto everyday work tasks like emails, summaries and analysis.
You leave with a compact framework for prompt clarity and iteration, plus worked patterns for emails, summaries and analysis.
None beyond the article — it works as a second pass over the same structural ideas.
Last reviewed: May 18, 2026
Continue through the same learning path with the next curated companion videos.
131 minutesYou can recognize when to follow up, when to switch models and when to start a fresh conversation, calibrated against real day-to-day usage.
131 minutesLearn to route work across fast, cheap, deep-reasoning and source-grounded tools instead of using one model for everything.
42 minutesSee how examples change model behavior and learn when few-shot prompting is worth the extra setup.
Hand-picked external courses that go deeper on this topic.
Dr. Jules White
The academic complement to DeepLearning.AI's short course — same discipline, longer arc, written for people who don't code. Dr. White teaches prompting as a set of reusable patterns (Ask for Input, Outline Expansion, Fact Check List, Menu Actions) rather than tricks. After this you'll prompt LLMs like a designer, not a guesser.
Isa Fulford · Andrew Ng
Ninety minutes to a year's worth of intuition. If you've started writing code that calls an LLM — or you're about to — this is the most efficient course online for closing the gap between "playing with ChatGPT" and "shipping a feature that calls an LLM."
Microsoft Learn
Prompt engineering, but for the tool most office workers will actually touch first. Microsoft's own four-part prompting framework (goal, context, source, expectation) is a genuinely useful mental model, and unlike the generic ChatGPT prompting courses already in our catalog, this one is grounded entirely in Microsoft 365 Copilot's specific quirks and grounding behavior.