Free Prompting Training: Become an AI Expert in 30 Days

What You'll Be Able to Do After the Training

By the end of this course, you'll master concrete skills that are directly applicable in your professional and personal daily life.

• Write Professional Prompts — Create structured prompts that generate usable results on the first try. No more rephrasing 5 times: you get exactly what you want, every time.
• Master 5+ AI Tools — ChatGPT, Claude, Gemini, Copilot, Midjourney — you'll know which tool to use for each task and how to adapt your prompts to each one's specifics.
• Automate Your Repetitive Tasks — Create reusable prompt templates for the emails, reports, analyses and presentations you do every week. Save 5 to 10 hours per week.
• Analyze and Synthesize Data — Extract relevant insights from any document, report or dataset using structured, reproducible analysis prompts.
• Create Quality Content — Write articles, LinkedIn posts, newsletters and presentations that captivate your audience, with a consistent style and optimized structure.
• Generate AI Images — Master the syntax of Midjourney, DALL-E and other image generation tools to create professional visuals in minutes.

How to Get Started? It's Simple and Immediate

No complex registration, no endless forms. Start your training journey in 3 simple steps.

Ready to Transform the Way You Use AI?

Every day without mastering prompting is a day you're wasting time, energy and opportunities. AI tools are here, free and powerful — the only thing missing is the skill to leverage them to their full potential. Start now with our interactive exercises or explore our ready-to-use templates. In 30 days, you'll look back and wonder how you ever managed without it.

• Start with interactive exercises for a progressive and structured skill development
• Explore the template library for immediate results on your current projects
• Use the prompt builder to create optimized prompts in just a few clicks
• Check the glossary whenever you encounter an unfamiliar term

Frequently Asked Questions About the Training

Have doubts? Here are the answers to the most common questions from our learners before getting started.

• Is it really 100% free? — Yes, entirely. All modules, exercises, templates and tools are accessible for free, with no credit card and no commitment. Our mission is to democratize access to AI skills for everyone.
• How long does it take to complete the training? — The full course represents approximately 20-25 hours spread across 5 modules. At 30 minutes per day, you can complete it in 30 days. But you can go faster or slower — what matters is your own pace.
• Do I need technical skills? — No, none at all. The training starts from the absolute basics and progresses gradually. If you know how to send a message in ChatGPT, you have all the skills needed to get started.
• Which AI tools is the training compatible with? — The techniques taught work with all major AI tools: ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Copilot (Microsoft), Midjourney, DALL-E, and many more. We indicate tool-specific features when they exist.
• Can I use these skills at work? — Absolutely, that's actually the main goal. Every technique and template is designed to be directly applicable in a professional context. Over 60% of our learners use the training to improve their workplace productivity.

The Complete Course: From Beginner to Expert in 5 Modules

Our training is organized into 5 progressive modules. Each module contains short theory lessons, hands-on exercises and templates to use immediately. You can follow the course in order or jump directly to the modules that interest you.

Who Is This Training For?

This training is designed for anyone who wants to use AI more effectively, regardless of their technical level. Here are the profiles that benefit the most.

• Professionals and Executives — You already use ChatGPT at work but feel you could go further. You want to save time on emails, reports, analyses and presentations. This training will multiply your productivity by 3 to 5x on these tasks.
• Entrepreneurs and Freelancers — You manage everything on your own: marketing, content, admin, customer service. AI used well becomes your best employee — available 24/7, fast, and versatile. Learn to effectively delegate to AI.
• Students and Researchers — Summaries, essays, literature reviews, data analysis: AI can accelerate your academic work while helping you develop critical thinking. Learn to use it ethically and effectively.
• Complete AI Beginners — You've heard about ChatGPT but don't dare to get started? This training begins with the absolute basics and guides you step by step. No technical skills required — just curiosity.

Why This Training Will Change Your Relationship with AI

The Art of Prompting is not a simple YouTube tutorial or a generic PDF. It's a structured, progressive and interactive course that transforms you from a complete beginner to an advanced AI user in 30 days. Every module is designed to be immediately actionable: you learn a technique, practice it in our interface, and see the result in real time. No useless theory, no incomprehensible jargon — just the skills you need to be more productive, more creative and more effective with AI.

• 100% free, no credit card, no commitment — start now and progress at your own pace
• Personalized learning path based on your level: beginner, intermediate or advanced, with an initial placement test
• Interactive hands-on exercises with real-time AI feedback — not just theory
• Ready-to-use prompt templates and models for every professional and personal situation
• Compatible with all AI tools: ChatGPT, Claude, Gemini, Copilot, Midjourney and more
• Active learner community to share, progress and stay motivated together

The complete program, step by step

Here is the detailed path you will follow: one method, five progressive modules, a work plan and concrete tools to turn theory into practice.

The Prompt Guide method: CRAFT-E

To improve without memorizing an endless list of techniques, use the CRAFT-E grid on every important prompt. It works as a quality check before testing an AI answer, then as an improvement grid after the test.

• Context: provide the situation, useful data, target audience and real constraints.
• Role: specify the expected expertise, but only when it truly changes how the model should answer.
• Action: state the task with a clear verb: analyze, compare, produce, correct, summarize or decide.
• Format: require a usable output: table, outline, checklist, JSON, email, brief or decision grid.
• Tests: add an example, counterexample or criterion that makes the result verifiable.
• Evaluation: ask the model to flag limits, uncertainty, assumptions and required human checks.

Short before/after example

CRAFT-E fill-in template

Use this template whenever a prompt must be reused, shared or integrated into a workflow. For a one-off question, three elements are often enough: context, action and format.

Tip: before adding an advanced technique, check the six CRAFT-E points first. Most weak prompts fail because they lack context, format or evaluation criteria.

Which path should you follow?

The core of the course stays the same: understand context, define the expected action, require a format and evaluate the answer. Then choose a priority track based on how you actually use AI.

• Complete beginner: start with what is prompting, then practice clarity and precision, providing the right context and defining the output format.
• Busy professional: follow modules 1 and 2, then use the prompt library to create three reusable templates tied to recurring work tasks.
• Marketing and content: use the digital marketing prompting guide, then adapt prompts for editorial planning, personas, campaigns and SEO review.
• Developer: start with the prompting guide for developers, then work on code review, test generation, documentation and bug analysis prompts.
• HR and recruiting: start from the HR and recruiting prompting guide, then practice producing a job description, interview rubric and structured candidate summary.

Progression rule

Do not jump straight to advanced prompts. For each profile, first validate a simple request, then a prompt with context, then a multi-step workflow. The reference is not how many prompts you copy, but your ability to get a reliable result twice in a row on a real case.

Expected output by profile

• Complete beginner: three simple prompts, each with an initial version and an improved version.
• Busy professional: three reusable templates for recurring tasks in your week.
• Marketing and content: a mini editorial plan, one campaign variant and a review checklist.
• Developer: a prompt pack for code review, test generation and documentation.
• HR and recruiting: a job description, interview rubric and structured candidate summary.

These outputs do not replace official proof, but they make your progress visible and reusable.

Module 1: strong prompting foundations

Start by understanding what an AI model needs from a prompt: intent, context, constraints and an output format. Recommended resources include the guide what is prompting, the clarity and precision exercise and the provide context exercise.

Module goal

Turn vague requests into usable instructions. This is the foundation that makes every advanced technique more effective.

Module 2: structure useful outputs

A strong AI answer depends as much on the requested format as on the question itself. Practice tables, action lists, outlines, JSON, briefs and checklists with the define the output format exercise, then explore the prompt library to study reusable structures.

Module goal

Get answers you can use directly instead of generic text that must be rewritten from scratch.

Module 3: intermediate techniques

Once the basics are solid, move to techniques that meaningfully change output quality: assigning a role, providing examples, constraining reasoning and asking for self-checks. Key exercises are role prompting, few-shot prompting and step-by-step reasoning.

Module goal

Adapt your prompt to the expected model behavior, expertise level and business context.

Module 4: professional applications

Prompting becomes truly useful when it fits a real job. Use the specialized guides to apply the method to marketing, development, HR, document analysis or personal productivity. Each guide should help you create a reusable prompt, not just obtain a one-off answer.

Module goal

Build a personal library of reliable prompts for recurring tasks.

Module 5: systems, agents and final project

To go beyond isolated prompts, combine prompts, constraints, examples, tools and AI agents. The recommended final project is to choose a real workflow, describe its goal, create three complementary prompts, test the outputs, then document the final version with its limits and success criteria.

Module goal

Move from a collection of prompts to a repeatable AI work system.

Recommended 4-week work plan

You can read the full course in one sitting, but the skill grows better through short cycles: learn, practice, test, correct. Use this simple rhythm to turn guides and exercises into real progression.

Week 1: foundations and clarity

Goal: write a clear and contextualized request. Read what is prompting, then complete the clarity and precision and provide the right context exercises.

Week 2: formats and examples

Goal: get answers you can use directly. Practice defining the output format, then turn three everyday requests into tables, checklists or structured briefs.

Week 3: advanced techniques

Goal: improve precision on more complex tasks. Practice role prompting, few-shot prompting and step-by-step reasoning, then compare results before and after each technique.

Week 4: real workflow

Goal: move from isolated prompt to reusable system. Choose a real work case, write three complementary prompts, test them twice, then document what works, what fails and which human checks are required.

Recommended time and final deliverable

Plan for 2 to 3 hours per week. By the end of the four weeks, you should have a mini prompt dossier: three complementary prompts, an improved version, a self-evaluation rubric and a list of limits that require human checking.

The sign that the path works is not that you read everything. It is that you can explain what changed between your first vague prompt and your final documented workflow.

Tip: keep a very simple learning log: date, goal, prompt tested, result, improved version. After four weeks, this log becomes your most useful proof of progress.

How to follow the course

1. Read a short guide to understand the concept.
2. Complete the related exercise and submit your answer to AI evaluation.
3. Compare your prompt with the success criteria.
4. Copy a nearby model from the prompt library.
5. Adapt it to a real use case in your work.

Tip: keep a record of your best prompts with the context, model used, result obtained and improved version. This iteration log is what turns learning into durable skill.

Self-evaluation rubric for a strong prompt

After each exercise or real case, score your prompt on six criteria. Use 0 if the criterion is missing, 1 if it is partial, 2 if it is clear and testable. A strong prompt reaches at least 9 out of 12 before you reuse it.

• Objective: the expected task is expressed as a precise action.
• Context: the prompt gives the situation, audience, useful data and constraints.
• Format: the expected output is directly usable: table, outline, checklist, JSON or brief.
• Examples: the prompt shows what is expected or what should be avoided.
• Success criteria: the result can be checked with explicit criteria.
• Limits: the prompt asks the model to flag uncertainty, assumptions and points that require human review.

How to interpret your score

Between 0 and 5, the prompt is still too vague. Between 6 and 8, it may work but can produce an answer that is hard to use. From 9 onward, you have a reusable base that you can improve through iterations.

Blocking criteria

The total score is not always enough. Do not reuse a prompt as-is if objective, context or limits score 0. These three points protect output quality, model understanding and human verification.

• Objective at 0: the model does not clearly know which task to complete.
• Context at 0: the answer may become generic or off-topic.
• Limits at 0: uncertainty, assumptions and human checks may disappear.

Tip: always keep the initial version and the improved version. The difference between them becomes your best learning material.

Why this course can become a reference

The best international courses share three traits: a clear path, lots of practice and visible progression. Prompt Guide already has the important building blocks: guides, AI-graded exercises, prompts and agents. The next step is to strengthen guided progression, level diagnostics, reviewed projects and public proof of skill.

The standards of a reference prompting course

The prompting market changes quickly. The best courses no longer stop at explaining how to write a good request: they help learners build a reusable, measurable method that adapts as tools evolve. Prompt Guide should be judged against these standards.

• Clear progression: start with the fundamentals, then move toward intermediate techniques, professional use cases and complete workflows.
• Immediate practice: connect every concept to an exercise or reusable prompt.
• Visible evaluation: learn to compare an AI answer against criteria such as clarity, context, format, constraints and reliability.
• Multi-model approach: understand what works with ChatGPT, Claude, Gemini, Mistral and other assistants without depending on one tool.
• Professional use cases: show how prompting applies to marketing, development, HR, research, analysis and productivity.
• Safety and limits: know when to verify, cite, anonymize data or choose another method instead of more prompting.
• Continuous updates: track model changes and revise examples when practices evolve.

Checklist for a truly complete module

A Prompt Guide module should not be considered finished just because it explains a concept. It is complete when the learner can move from understanding to proof of use.

• Observable objective: the learner knows what they should be able to do by the end.
• Exercise or reusable prompt: the concept is tested on a concrete task.
• Quality criterion: the result can be evaluated with simple criteria.
• Deliverable: the learner produces a sheet, prompt, workflow or documented improvement.
• Limit: the module says when to verify, anonymize, cite or ask for human validation.
• Update trace: examples can be revised when models or practices change.

Tip: to evaluate your level, do not only ask whether your prompt produces a correct answer. Ask whether the result is repeatable, controllable and useful in your real work context.

Which AI model should you use to practice prompting?

Prompting should not depend on a single tool. The principles of clarity, context, format, constraints, examples and evaluation work with ChatGPT, Claude, Gemini, Mistral and other AI assistants. What changes is how each model reacts to your instructions.

To learn the basics

Choose the model you can access easily and keep using the same one for a few exercises. You will see more clearly the effect of each prompt change.

To compare results

Test the same prompt on two different models. Compare precision, structure, omissions, refusals, level of detail and how easy it is to improve the answer.

For professional tasks

Choose based on context: document length, coding needs, language, web access, data confidentiality, available integrations and your organization’s rules.

To make real progress

Keep a record of the model used, prompt version, result obtained and correction applied. This comparison teaches you to distinguish a strong method from a lucky result.

Tip: do not look for the perfect model before practicing. First learn to write a clear prompt, then observe how each assistant responds to the same frame.

Essential prompting glossary

To progress quickly, learners need shared vocabulary. These terms appear throughout the course and in most professional AI use cases.

• Prompt: an instruction given to an AI model to obtain a response.
• Context: information that helps the model understand the situation, goal, audience and constraints.
• Role: the stance you ask the model to adopt, such as analyst, instructor, senior developer or marketing lead.
• Output format: the expected structure of the answer, such as a checklist, table, plan, JSON object or sectioned summary.
• Few-shot prompting: a technique where you provide one or more examples to guide style, level of detail or format.
• Iteration: progressive improvement of the prompt after observing the result.
• Success criterion: a condition that tells you whether the answer is usable, complete and adapted to the context.
• Hallucination: an answer that looks plausible but is false, invented or insufficiently verified.
• AI agent: an assistant configured to follow a role, goal, instructions and sometimes tools in a recurring workflow.
• Evaluation: comparison of an AI answer against explicit criteria before using it.

Note: learning these terms is not enough. Real progress starts when you use them to review your own prompts: what context is missing, what format is expected, what criterion validates the result?

Before/after examples: turn an average prompt into a useful one

Prompting progress becomes clearer when you compare a vague request with a structured version. The examples below show how to add the goal, context, format and success criteria.

Example 1: marketing writing

Before: write a LinkedIn post about our new product.

After: you are a B2B marketing manager. Write a 120 to 160 word LinkedIn post announcing a SaaS tool that helps HR teams automate candidate screening. Audience: HR leaders in small and medium businesses. Tone: professional, concrete, no jargon. Structure: hook, problem, benefit, use case example, invitation to comment.

Why it is better: the model knows the role, audience, context, length, tone and expected structure.

Example 2: document analysis

Before: summarize this document.

After: analyze the document below for an executive who needs to decide quickly. Produce a five-point summary, then list the risks, decisions to make and missing information. If a conclusion is not supported by the document, say so clearly.

Why it is better: the prompt specifies the reader, the output type and the caution rule for uncertain information.

Example 3: development

Before: fix my code.

After: act as a senior TypeScript developer. Review this React component and identify likely bugs, typing risks and edge cases. Start with critical issues, then secondary improvements. For each point, explain the impact and propose a short fix.

Why it is better: the AI knows what to check, how to order the answer and what level of detail to provide.

Tip: when a prompt fails, do not change everything. Add one element at a time: context, format, constraint, example or evaluation criterion. You will understand faster what really improves the answer.

Common prompting mistakes and fixes

A strong prompting course should also teach learners how to recognize mistakes. When an AI answer is disappointing, the issue often comes from missing context, an unclear goal or no output format. Fixing those points is often enough to improve the result significantly.

Mistake 1: asking for an answer without defining the goal

Symptom: the answer is correct but too generic.

Fix: add the decision, action or deliverable the answer should help produce.

Example: instead of asking for a market analysis, ask for an analysis meant to choose between three priority segments, with criteria and a final recommendation.

Mistake 2: forgetting the audience

Symptom: the tone, vocabulary or level of detail is wrong.

Fix: specify who will read the answer, what they know and what they expect.

Example: an explanation for an executive committee should not have the same structure as a beginner tutorial.

Mistake 3: not giving an output format

Symptom: you get a long text that is hard to use.

Fix: explicitly ask for a list, table, plan, checklist, JSON object or sectioned summary.

Example: to compare tools, ask for a table with criteria, benefits, limits and recommended use case.

Mistake 4: changing everything at once

Symptom: you no longer know which change improved or degraded the result.

Fix: iterate on one parameter at a time: context, role, constraint, example or format.

Example: keep the same prompt and test only the addition of one example of the expected answer.

Mistake 5: trusting the answer without checking it

Symptom: the answer sounds fluent but contains approximations, omissions or unsupported claims.

Fix: ask for assumptions, limits, points to verify and needed sources when the topic is sensitive.

Example: for legal, medical, financial or regulatory analysis, use AI as preparation support, not as the final authority.

Tip: keep a list of your recurring mistakes. It will become your personal checklist before sending an important prompt.

Build a prompt portfolio

To make prompting a visible skill, keep a record of your best cases. A prompt portfolio does not need to be public or complex: it should show the problem, prompt, result, improvement and limits.

What each entry should include

• Context: task, audience, constraints and AI model used.
• Initial prompt: first version, even if imperfect.
• Result obtained: what works, what is missing and what must be checked.
• Improved version: corrected prompt with context, format, examples or criteria.
• Success criterion: simple indicator that proves the answer is usable.
• Limits: missing data, risks, assumptions and points that need human review.

Three entries to create during the course

1. A personal productivity prompt, such as a summary, action plan or prioritization.
2. A professional prompt, such as marketing, HR, analysis, customer support, code or research.
3. A critical prompt, where you mainly document checks, limits and risks.

This portfolio becomes your personal proof of progress. It can also help train a team, prepare for an interview, create an internal library or decide which prompts are worth automating.

Tip: do not keep only prompts that worked immediately. Corrected prompts are often the most useful because they show your analysis and improvement method.

Going further: the advanced modules

Once you have completed this path, go deeper with our advanced guides: workflows, AI agents and multimodal, security, verification and responsible use, and team prompting: workshop, maintenance and benchmark.

Resources Included for Free

In addition to the training modules, you have access to a complete ecosystem of tools and resources to accelerate your progress.

• 50+ Interactive Exercises — Exercises sorted by level and category, with automatic grading and improvement suggestions. Each exercise is based on a real use case so that practice is immediately transferable to your daily life.
• 100+ Prompt Templates — A library of ready-to-use templates for every situation: professional email, data analysis, content creation, brainstorming, code review, and much more. Each template is customizable and comes with usage examples.
• Interactive Prompt Builder — A unique tool that guides you step by step through building your prompts. Select your objective, define your constraints, and the builder generates an optimized prompt you can copy-paste directly into any AI tool.
• Complete Prompting Glossary — Over 80 terms explained simply with concrete examples. From 'zero-shot' to 'hallucination' to 'temperature' and 'token', all AI vocabulary demystified.
• Downloadable Cheat Sheet — A condensed cheat sheet with best practices, shortcuts and key prompting formulas. Keep it handy for your AI work sessions.
• Prompting Recipes — Pre-designed prompt combinations for complete workflows: writing an article from A to Z, preparing an interview, analyzing a market, creating a presentation. Follow the recipe, get the result.

What Our Learners Say

Thousands of people have already transformed the way they use AI through this course. Here are some representative testimonials.

• Marie L., Marketing Manager — Before the training, I spent 2 hours writing my newsletters. Now, with the templates and techniques I learned, I produce better content in 30 minutes. The content prompting module was a revelation.
• Thomas R., Full-Stack Developer — I thought I was already using ChatGPT well for coding. The advanced module introduced me to techniques like chain of thought and mega-prompting that completely changed how I debug and architect my projects.
• Sophie D., Master's Student — The prompt builder is incredible for my academic research. I learned to structure my synthesis and analysis requests in the most effective way. My productivity tripled.
• Marc P., E-commerce Entrepreneur — The digital marketing prompting recipes allowed me to create product descriptions, Facebook ads and follow-up emails in a fraction of the time. Immediate ROI on my business.

Conclusion

Prompting is not a passing trend — it's the fundamental skill of the artificial intelligence era. Those who master it today gain a considerable advantage over those who wait. Our free training gives you everything you need: theory, practice, tools and templates. The only missing ingredient is you. Start now — your future self will thank you.