Update post-lecture quiz link in README.md

1-Introduction/02-ethics/README.md

@@ -247,7 +247,7 @@ Note that there remains an intangible gap between _compliance_ (doing enough to
 The latter requires [collaborative approaches to defining ethics cultures](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f) that build emotional connections and consistent shared values _across organizations_ in the industry. This calls for more [formalized data ethics cultures](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) in organizations - allowing _anyone_ to [pull the Andon cord](https://en.wikipedia.org/wiki/Andon_(manufacturing)) (to raise ethics concerns early in the process) and making _ethical assessments_ (e.g., in hiring) a core criteria team formation in AI projects.
 
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-## [Post-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/3) 🎯
+## [Post-lecture quiz](https://ff-quizzes.netlify.app/en/ds/) 🎯
 ## Review & Self Study 
 
 Courses and books help with understanding core ethics concepts and challenges, while case studies and tools help with applied ethics practices in real-world contexts. Here are a few resources to start with.