For a free certification: the result of the MOOC evaluation will do.
If we want something more official, there will have to be some kind of fee to setup a service to control that there is no cheating when taking the test. And this kind of controlled testing platform is not free.
But honestly, if you want to show your knowledge of scikit-learn to potential employers, it’s much better to:
- publish a few original Python code or notebooks files of your own on a public repository, for instance as a github repository, showcasing your understanding of scikit-learn to solve an original data science problem of your choice;
- prepare a short, e.g. 5 to 10 min presentation, possibly recorded as a video (on youtube), where you discuss your results, the choice of the metrics, the choice of the cross-validation strategy, the features engineering decision and emphasize the limits of your model and the data to show your critical understanding of the machine learning tools in a given application context.
And then link to that in your application / cover letter as some kind of data scientist / ML engineer portfolio.
To summarize, it’s more important to be able to demonstrate that your understand the concepts taught in the MOOC than to focus on getting certifications. Potential employers do not necessarily know the content of MOOCs and certifications. But they can hopefully quickly assess the level of maturity of candidates by reviewing one or two notebooks and a short video presentation.
Paid certifications and free MOOC quizzes are primarily useful to you: to build some trust that you properly understood the most important concepts taught in the MOOCs and that you did not miss any important detail or potential pitfall.