Official pages: Google Cloud, Anthropic, OpenAI and DeepLearning.AI (screenshots, Oct 25, 2026)
I have worked in IT for about twenty years, and the question I hear most since AI chat tools went mainstream is "how do I get it to give me something useful?" The honest answer is that the skill is less about secret phrases and more about good briefing, the same habit that makes a ticket or a spec easy to act on. This guide follows what people search next on Google (what a prompt is, free courses, certificates, the IBM course on Coursera, the DeepLearning.AI course) and answers each one using the official guides from Google Cloud, OpenAI and Anthropic and the course pages themselves.
Quick answer- A prompt is the input you give an AI model. Google Cloud's guide says its quality directly influences how relevant the output is.
- The habits all three vendors agree on are clear instructions, useful context, examples, and trying again with changes.
- For a free structured start, the DeepLearning.AI course is listed as beginner level, about 1h40m, and its page says access is free for a limited time during the platform beta.
- For a certificate-style course, the IBM course on Coursera lists a shareable certificate, but the page pushes a subscription or trial, so check what you get before you pay.
Jump to: What is a prompt | Basics | Techniques | Free course | IBM on Coursera | Google | Certificates | Examples | Compare | FAQ
General information for learners. Tool names, model names and course details change quickly, so check each linked page before you rely on it. Prompt examples in this article are ones I wrote as illustrations and I have not run them against any model.
Disclosure: As an Amazon Associate I earn from qualifying purchases. Some links on this page are affiliate links, at no extra cost to you. The AI tools themselves are not affiliate links.
What Is a Prompt?
Image: Google Cloud (official page, screenshot Oct 25, 2026)
Google Cloud defines a prompt as the input you give a model to get a specific response. It can be a simple question or keyword, or a complex instruction, code snippet or writing sample. The same page describes prompt engineering as the art and science of designing and optimizing prompts to guide models toward the response you want. The version I read shows "Last Updated: 05/04/2026".
Image: Google Cloud (official page, screenshot Oct 25, 2026)
OpenAI puts it in similar terms: prompt engineering is writing effective instructions so a model consistently generates content that meets your requirements. It adds a warning that matters for beginners. Model output is non-deterministic, so getting what you want is "a mix of art and science", and different model types, even different snapshots of the same family, can respond differently to the same prompt.
My take (20 years in IT): Treat a prompt like a work request to a smart colleague who was not in the meeting. If a person with no context could not do the job from your message, a model probably cannot either. That one test fixes most weak prompts.
AI Prompt Engineering Basics: Six Habits That Show Up in Every Guide
Google Cloud lists strategies for writing better prompts, and OpenAI and Anthropic say much the same in their own words. Here are the six that overlap most.
- Say what you want and how it should look. Google suggests using action verbs, defining the length and format, and naming the audience.
- Be specific. Google's examples replace "write something about climate change" with a defined task, and suggest quantifying requests and breaking big tasks into steps.
- Give context. Include relevant facts, point to the source document, and define key terms. Anthropic adds that explaining why you want something helps the model aim better.
- Show examples. Anthropic calls examples one of the most reliable ways to steer format, tone and structure, and says to make them relevant, diverse and clearly separated from your instructions.
- Structure the prompt. OpenAI suggests Markdown headers and lists, and XML tags, to mark where instructions, examples and reference text begin and end. Anthropic gives the same advice for XML tags.
- Iterate. Google recommends trying different phrasings, adjusting the level of detail and testing different prompt lengths.
Image: Anthropic (official docs page, screenshot Oct 25, 2026)
Anthropic's overview adds a step that many tutorials skip. It assumes you already have a clear definition of success, a way to test against it, and a first draft prompt, and it says not every failing result is best fixed by prompting. Sometimes a different model is an easier fix for speed or cost. That is the engineering part of prompt engineering: decide how you will judge the output before you start tweaking words.
Image: Anthropic (official docs page, screenshot Oct 25, 2026)
The same page links to two interactive tutorials, one on GitHub and one in Google Sheets. Anthropic says the tutorial was written for Claude 3 models and tells readers to follow its prompting best practices page where the two differ, so use the tutorial for fundamentals and the best practices page for current advice.
Prompt Engineering for Generative AI: Zero-Shot, Few-Shot and Step by Step
Image: Google Cloud (official page, screenshot Oct 25, 2026)
Google Cloud names four common prompt types. Zero-shot gives a direct instruction with no examples, such as summarizing or translating. One-, few- and multi-shot prompts include one or more input and output pairs first. Chain of thought prompts ask the model to work through intermediate reasoning steps. Zero-shot chain of thought combines both by asking for reasoning steps without examples.
Image: OpenAI (official docs page, screenshot Oct 25, 2026)
OpenAI's guide describes few-shot learning as including a handful of input and output examples so the model picks up the pattern, and suggests showing a diverse range of inputs. It also describes a layout for the developer message: identity, instructions, examples, then context, with changing context usually placed near the end. For reasoning models it offers an analogy. A reasoning model is like a senior coworker you can give a goal, while a standard GPT model is like a junior coworker who does best with explicit instructions.
Image: Anthropic (official docs page, screenshot Oct 25, 2026)
Anthropic's best practices page has a simple test: show your prompt to a colleague with minimal context and ask them to follow it. If they would be confused, the model will be too. It also advises telling the model what to do rather than what not to do, and putting long documents near the top of the prompt, above your question.
Image: Anthropic (official docs page, screenshot Oct 25, 2026)
AI Prompt Engineering Course Free and the DeepLearning.AI Option
Image: DeepLearning.AI (official course page, screenshot Oct 25, 2026)
The DeepLearning.AI course "ChatGPT Prompt Engineering for Developers" is taught by Isa Fulford of OpenAI and Andrew Ng. The page lists it as a beginner short course of about 1h40m with 9 video lessons and 7 code examples, and shows "Updated Oct 12, 2026". It covers guidelines, iterating on prompts, summarizing, inferring, transforming, expanding and building a chatbot. The page says only a basic understanding of Python is needed.
Image: DeepLearning.AI (official course page, screenshot Oct 25, 2026)
On the free question, the page says "Course access is free for a limited time during the DeepLearning.AI learning platform beta." It also lists a graded assignment and an accomplishment as part of the PRO plan. I cannot tell you how long the free period lasts, so open the page and check before you plan around it.
Image: DeepLearning.AI (official course page, screenshot Oct 25, 2026)
Who should pick the DeepLearning.AI course Developers and the curiousYou are comfortable reading a little Python and want hands-on practice with the API. Skip it if you want a no-code course, because the page expects basic Python and the examples run in a notebook.
My take (20 years in IT): Pick a course by what you will do with it. If you will write code against an API, a developer course is worth the hour or two. If you only want better answers from a chat window, the vendor guides on this page cover most of the same ground for free.
Generative AI Prompt Engineering Basics on Coursera From IBM
The Coursera course "Generative AI: Prompt Engineering Basics" is offered by IBM and taught by Antonio Cangiano. The page lists it as beginner level with 3 modules and 5 assignments, a shareable certificate, English instruction and a flexible schedule. Its learning goals are to explain what prompt engineering is, apply best practices for creating prompts, assess commonly used prompt tools, and apply common techniques. The page also says you can master prompt engineering in about 9 hours with no coding required, and elsewhere suggests one week at 10 hours a week.
When I read the page it showed 693,791 enrolled learners and 8,171 reviews, and its review breakdown showed 81.31 percent five-star ratings. Those numbers come from Coursera's own page, so treat them as Coursera's figures.
Is it free? The page I read shows the course as included with Coursera Plus and offers a subscription trial. I did not see a clear free option on it, so I cannot tell you that it is free. Check the enroll button and any "audit" or financial aid option on the page itself.
About "Coursera answers". People search for quiz answers, and I understand the time pressure, but I will not point you to them. Course quizzes exist to check what you learned, and copied answers can break a platform's honor code and leave you with a certificate you cannot defend in an interview.
Who should pick the IBM course No-code beginnersYou want a structured, no-code overview with a certificate at the end. Skip it if you only need the basics for your own use, since the free vendor guides above cover the same techniques, and check the price before you start.
Google AI Prompt Engineering Course? What I Could and Could Not Verify
Image: Google Cloud (official page, screenshot Oct 25, 2026)
This is a popular search term, so here is what I actually checked. I read Google Cloud's prompt engineering guide, which is an article, not a course. It includes tables of example prompts for creative writing, summarization, translation, question answering, code generation and image generation. I did not open a Google course page, so I will not describe one, its length, or whether it offers a certificate.
Image: Google Cloud (official page, screenshot Oct 25, 2026)
The Google guide's table of question types is a handy way to practice. It separates open-ended questions, specific questions, multiple choice, hypothetical questions and opinion-based questions, each with a sample prompt.
AI Prompt Course Free With Certificate: What to Expect
Of the two courses I read, the IBM course on Coursera lists a shareable certificate and the DeepLearning.AI page ties its graded assignment and accomplishment to a PRO plan. That does not tell you what a certificate costs or whether any employer values it. I found no source that says so, and I have not seen hiring data. A reasonable plan is to learn the skill from the free guides, then pay for a certificate only if a specific employer or program asks for one.
Image: Anthropic (official docs page, screenshot Oct 25, 2026)
Worked Examples You Can Copy (My Illustrations, Not Tested)
These short examples apply the habits above. I wrote them as illustrations. I have not run them against any model, so adjust them and judge the output yourself.
Weak promptWrite about our new project.
Improved prompt (goal, audience, format, constraints)You are helping me write an internal update.
Task: Summarize the project notes below for our sales team.
Audience: sales reps with no technical background.
Format: five bullet points, then one sentence on what sales should do next.
Length: under 120 words.
<notes>
[paste notes here]
</notes>
Few-shot prompt (two examples, then your input)Turn each customer message into a short ticket title.
Message: "I was charged twice for my March invoice."
Title: Duplicate charge on March invoice
Message: "The app logs me out every few minutes on my phone."
Title: Frequent logout on mobile app
Message: "[new customer message]"
Title:
Step by step promptReview the draft below. First list the three weakest claims and why. Then suggest one fix for each. Do not rewrite the whole draft.
<draft>
[paste draft here]
</draft>
My take (20 years in IT): Two safety habits go with every prompt. Do not paste passwords, client data or anything confidential into a tool unless your organization has approved it, and always check facts, numbers and quotes the model gives you before you use them.
Quick Comparison of the Resources
| Resource | Format | Level and notes | Watch out for | Link |
|---|
| Google Cloud prompt engineering guide | Article with example tables | Page shows Last Updated 05/04/2026 | Not a course, no certificate | Visit site |
| OpenAI prompt engineering guide | API documentation | Aimed at developers using the API | Model names and APIs change | Visit site |
| Anthropic prompt engineering overview and best practices | Documentation and tutorials | Assumes you can test results | Tutorial was written for Claude 3 models | Visit site |
| DeepLearning.AI ChatGPT Prompt Engineering for Developers | Short course, about 1h40m | Beginner, basic Python needed | Free only for a limited time, graded assignment is PRO | Visit site |
| IBM Generative AI Prompt Engineering Basics on Coursera | Course, 3 modules | Beginner, no coding, certificate listed | Subscription or trial on the page | Visit site |
How to Choose Where to Start
Final Recommendation
Frequently Asked Questions
What is prompt engineering in simple terms?
It is writing clear, specific instructions for an AI model so it reliably gives you the kind of output you need. OpenAI describes it as writing effective instructions so a model consistently generates content that meets your requirements.
Do I need to code to learn prompt engineering?
Not for the basics. The IBM course on Coursera says no coding is required. The DeepLearning.AI course page says a basic understanding of Python is needed.
Are there free prompt engineering courses?
The DeepLearning.AI page says access is free for a limited time during its platform beta. The Google Cloud, OpenAI and Anthropic guides were readable on their public pages when I checked. I did not see a clear free option on the IBM Coursera page, so check it directly.
Does a prompt engineering certificate help me get a job?
I found no source that says so. The IBM course lists a shareable certificate, but I have no hiring data. Treat a certificate as optional and keep examples of your own work.
Will the same prompt work in ChatGPT, Claude and Gemini?
Not always. OpenAI notes that different model types and even different snapshots can respond differently, and Anthropic advises re-checking any technique against your own tests before applying it to another model.
Try These Resources
These are plain links. This blog has no affiliate relationship with any of them.
Sources
- Google Cloud, Prompt engineering overview and guide (page shows Last Updated 05/04/2026), read October 25, 2026
- OpenAI, Prompt engineering guide, read October 25, 2026 (the page shows no date)
- Anthropic, Prompt engineering overview, read October 25, 2026
- Anthropic, Prompting best practices, read October 25, 2026
- DeepLearning.AI, ChatGPT Prompt Engineering for Developers (page shows Updated Oct 12, 2026), read October 25, 2026
- Coursera, Generative AI: Prompt Engineering Basics (IBM), read October 25, 2026
Screenshots are of the official pages named in each caption, framed here, and belong to their owners.
Last updated: October 25, 2026.
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