Get the Most Out of This Course
Before you learn to take a tool apart and weigh what could go wrong with it, take a few minutes to see the whole picture: what this course gives you, how it is built, and how to work through it so the skill actually sticks. A little orientation now makes every chapter that follows easier to use.
Discover the Course Objectives
Almost every part of life now runs through a digital or AI tool: an app that manages your money, a service that recommends what to watch or who to date, an assistant that drafts your messages, a smart device in your home. When a tool works well, it feels effortless. When it goes wrong, it can quietly overcharge you, treat some people unfairly, leak private information, or cause real harm, and often no one notices until the damage is done.
This course builds the skill of looking hard at a tool before and while you trust it. You will learn to take a real, everyday tool, name the risks it carries, judge how likely and how serious each one is, decide what to do about each, and reach a clear recommendation you can defend, even when you do not have every fact.
The point is not to memorize theory. It is to walk away with a method you can apply to a real tool of your own, whether that is a budgeting app, a community AI assistant, a health tracker, or a civic service. Wherever people rely on a digital or AI tool to make a decision or handle their information, this is the skill that keeps that reliance responsible.
By the end of this course, you will be able to:
Run a complete risk review on a digital or AI tool: identify, assess, prioritize, respond, and justify.
Assess each risk by its likelihood and its impact, then use that to prioritize a mixed set of risks.
Choose a proportionate response to each risk: avoid, reduce, accept, or escalate.
Map how a tool handles personal data: what it collects, where it goes, who can reach it, how long it is kept, and whether consent is clear.
Reach and justify a responsible recommendation under uncertainty, defending one knowingly accepted residual risk.
Meet Your Teacher
This course was created by the OpenClassrooms Team with the help of artificial intelligence.
Discover the Course Plan
This course is one focused part, and it follows a deliberate order built around a single method: a risk review.
A risk review moves through five steps. You identify the risks a tool carries, assess how likely and how serious each one is, prioritize them so you know which few matter most, respond to each with a proportionate action, and finally justify the overall recommendation you reach. Each chapter takes you one step further along that sequence, from building the vocabulary you need, to prioritizing and matching responses, to deciding and defending a full recommendation, and then practicing the whole method on a compact case of your own.
The steps are in this order for a simple reason: you cannot weigh or respond to a risk you have not yet named, and you cannot defend a recommendation you have not yet reasoned through. Naming and assessing first gives you the clear picture you need before you commit to a decision. If you have already explored how AI or security can go wrong through the optional companion courses, this method is where those separate concerns come together into one review.
Know What You Need to Begin
You need no prior experience with technology, no special software, and no background in AI or security. This course is written for true beginners, and every new term is defined the first time it appears.
Everything you practice can be done using only information anyone can find: an app’s public description, its privacy policy, its reviews, and how it behaves when you use it. You will never be asked to use a paid audit tool, a private work system, or insider access, so you can follow along whatever your situation.
If you would like extra background, two optional companion courses sit comfortably beside this one: Destination AI: Introduction to Artificial Intelligence, which builds a healthy sense of what AI can and cannot be trusted to do, and Discover the World of Cybersecurity, which explains how attacks and security failures happen. Neither is required to start, and this course defines what it needs as it goes.
Get the Most Out of Each Chapter
Work through the chapters in order. Each one builds on the last, and the method only holds together when the pieces connect.
Read the worked examples closely. They walk through the method on real, everyday tools, from a health app to a community assistant, so you can see each move in action before you try it yourself. When you reach a practice prompt, attempt it before you check the model solution provided at the end of that chapter. The thinking you do on your own is where the learning actually happens.
The course also ends with a short quiz. This check is there only for you: it helps you confirm what has landed and spot what to revisit. Nothing is graded, so use it honestly rather than anxiously.
Take your time, stay curious, and keep testing each move against your own tool. By the end you will have a method you trust for weighing the risks of any digital or AI tool, and the confidence to make a call you can defend.
With the big picture in view, let’s begin the method itself by building the core vocabulary of risk and walking through the five steps of a risk review.
