Prompt Engineering for Engineers

Yes, but the useful part is not clever wording. It is defining what a correct answer looks like and testing the prompt against it. Anthropic's own documentation for Claude says that before prompt engineering you should have a clear definition of the success criteria for your use case. You also need some way to test empirically against those criteria. That is the habit this course builds. It ends with a prompt that is checked against a golden set and given a score.

Run it against a fixed set of inputs whose correct outputs you already know, and score how many it gets right. OpenAI's developer documentation calls these tests evals. It describes them as testing model outputs to ensure they meet style and content criteria that you specify. In the course you test a prompt against ten or more cases with known answers and iterate to a score. You also score a tag-list converter by exact match.

Give it the source data, tell it to use only that data, and give it a way to say information is missing. Anthropic's guide to reducing hallucinations recommends allowing the model to say I don't know. It also recommends grounding answers in direct quotes and verifying claims with citations. These techniques reduce hallucinations but do not eliminate them. The course applies the idea to documents and code generated from data tables. You still check the output.

No. It works in ChatGPT, Claude, Gemini, Copilot or any model through an API, and the point is the discipline of specifying, constraining and testing, not the tool. Every module ends with a prompt you keep.

Not to start. Most modules need no code. The scoring examples (module 8 most of all) use a few lines of Python that are given to you, and a couple of optional pages use a little more; if you have never coded, paste the code or score by hand in a spreadsheet.

You take one document you actually produce, such as a FAT report section, a procedure or a fault-code guide. You build the prompt that generates it from a table and test it against ten or more cases with known answers. You iterate to a score. Then you write it up as a prompt-library entry a colleague could reuse. A second short project scores a tag-list converter by exact match.

No. Any free chat tool works for most modules, and the scoring modules use OpenRouter's free models with a free key.

Yes. Every module, practice task, project and assessment. You create an account so your progress is saved and the assessments can be marked. The certificate is the only paid item, and only if you want it.

An EDWartens Certificate of Completion, issued when you have finished the modules and passed the final assessment (the project is optional practice), with a verification code anyone can check. It is not a vendor credential and is never described as one.

The creators named in the Credits block at the foot of this page, on their own YouTube channels. EDWartens did not make the videos and the creators are not affiliated with EDWartens. What EDWartens wrote is the study plan, the notes, the practice tasks, the projects and the assessments.

No. The lab is optional practice. You can skip it whenever you like, and it never blocks your progress, the final assessment or your certificate.

Yes. Every lab level for this course opens in your browser, free, with nothing to install.

The Prompt Engineering for Engineers course has 12 modules. It opens with "A prompt is a specification", goes through "Zero-shot, one-shot and few-shot examples", "Structured output: JSON and tables", "Prompting for code" and "Safety, confidentiality and injection" and ends with "Final assessment". The full list with minutes is under "What you learn" on this page.

After the Prompt Engineering for Engineers course: Write a five-part prompt with a refusal rule that turns invention into a visible blank; Fix output format with few-shot examples and get JSON with a schema at temperature 0; Make calculations checkable with chain of thought, and run the arithmetic as code. These are the practical outcomes the course is written around, and the final assessment of 15 questions checks them.

For the Prompt Engineering for Engineers course, software: Any chat tool (ChatGPT, Claude, Gemini, Copilot) or Google Colab with a free OpenRouter key. Hardware: none. The course itself is free.

Prompt Engineering for Engineers is rated beginner. Beginner. No coding required for most modules; the scoring examples use a few lines of Python you can paste. It is written for engineers, developers and students applying AI to real work, and takes about 13.2 hours at your own pace.

Skills from the Prompt Engineering for Engineers course (for example: write a five-part prompt with a refusal rule that turns invention into a visible blank) are used in roles such as AI engineer, machine learning engineer, data analyst and automation developer, and in machine learning engineer work. The course gives you practical evidence of the skill; it does not promise a job, and employers decide on experience and interview.