Prompt Engineering Academy · Beginner
① Prompt Foundations
The mental model that makes everything else make sense: how models read a prompt, what a clear ask looks like, why context is half the job, how to control the shape of the output, and the iteration loop that turns an okay answer into the right one. 5 sections · quizzes with fresh questions every attempt · 1 capstone.
What you'll be able to do
- Explain, in plain language, how an AI model reads and completes a prompt.
- Write asks that state the task, the audience, the constraints, and the output shape.
- Decide what context to include, what to summarize, and what to leave out.
- Control length, format and structure instead of accepting whatever arrives.
- Run a deliberate iteration loop instead of re-rolling and hoping.
Grading: Section quizzes 60% · final test 40% · capstone graded by rubric (self-assessed)
Prerequisites: None. If you have ever typed a question into ChatGPT, Claude or Gemini, you are ready.
Your progress
0%, slides read (30%) + best quiz scores (70%), final counts double. Stored in this browser.
Start / continue →Sections
1
How AI Reads Your WordsThe one mental model that explains most prompt behavior: completion, context, and why the model can't read your mind.
2
The Anatomy of a Clear AskTask, audience, constraints, output shape, the four-part skeleton that upgrades almost any prompt.
3
Context Is the Half You're Not WritingWhat to include, what to summarize, what to leave out, and why dumping everything is as bad as dumping nothing.
4
Controlling the OutputLength, structure, format and 'what good looks like', the difference between receiving an answer and specifying one.
5
The Iteration LoopFirst drafts are the model's opening bid. The loop, critique, constrain, continue, is where good outputs actually come from.
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Final test + capstone
10 questions across the whole course, then the applied capstone brief.