Fix Quiz link

Author: leestott

1-Introduction/01-defining-data-science/README.md

@@ -8,7 +8,7 @@
 
 [![Defining Data Science Video](images/video-def-ds.png)](https://youtu.be/beZ7Mb_oz9I)
 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/0)
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/0)
 
 ## What is Data?
 In our everyday life, we are constantly surrounded by data. The text you are reading now is data.  The list of phone numbers of your friends in your smartphone is data, as well as the current time displayed on your watch. As human beings, we naturally operate with data by counting the money we have or by writing letters to our friends.

1-Introduction/02-ethics/README.md

@@ -21,7 +21,7 @@ In this lesson, we'll explore the fascinating area of data ethics - from core co
 
 
 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/2) 🎯
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/2) 🎯
 
 ## Basic Definitions
 

1-Introduction/03-defining-data/README.md

@@ -8,7 +8,7 @@ Data is facts, information, observations and measurements that are used to make
 
 This lesson focuses on identifying and classifying data by its characteristics and its sources.
 
-## [Pre-Lecture Quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/4)
+## [Pre-Lecture Quiz](https://ff-quizzes.netlify.app/en/ds/quiz/4)
 ## How Data is Described
 
 ### Raw Data

1-Introduction/04-stats-and-probability/README.md

@@ -9,7 +9,7 @@ Statistics and Probability Theory are two highly related areas of Mathematics th
 [![Intro Video](images/video-prob-and-stats.png)](https://youtu.be/Z5Zy85g4Yjw)
 
 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/6)
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/6)
 
 ## Probability and Random Variables
 

2-Working-With-Data/07-python/README.md

@@ -26,7 +26,7 @@ We will focus on a few examples of data processing, instead of giving you full o
 
 
 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/12)
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/12)
 
 ## Tabular Data and Dataframes
 

2-Working-With-Data/08-data-preparation/README.md

@@ -4,7 +4,7 @@
 |:---:|
 |Data Preparation - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
 
-## [Pre-Lecture Quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/14)
+## [Pre-Lecture Quiz](https://ff-quizzes.netlify.app/en/ds/quiz/14)
 
 
 

3-Data-Visualization/09-visualization-quantities/README.md

@@ -5,7 +5,7 @@
 | Visualizing Quantities - _Sketchnote by [@nitya](https://twitter.com/nitya)_ |
 
 In this lesson you will explore how to use one of the many available Python libraries to learn how to create interesting visualizations all around the concept of quantity. Using a cleaned dataset about the birds of Minnesota, you can learn many interesting facts about local wildlife. 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/16)
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/16)
 
 ## Observe wingspan with Matplotlib
 

3-Data-Visualization/10-visualization-distributions/README.md

@@ -6,7 +6,7 @@
 
 In the previous lesson, you learned some interesting facts about a dataset about the birds of Minnesota. You found some erroneous data by visualizing outliers and looked at the differences between bird categories by their maximum length.
 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/18)
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/18)
 ## Explore the birds dataset
 
 Another way to dig into data is by looking at its distribution, or how the data is organized along an axis. Perhaps, for example, you'd like to learn about the general distribution, for this dataset, of the maximum wingspan or maximum body mass for the birds of Minnesota. 

3-Data-Visualization/11-visualization-proportions/README.md

@@ -170,7 +170,7 @@ In this lesson, you learned three ways to visualize proportions. First, you need
 ## 🚀 Challenge
 
 Try recreating these tasty charts in [Charticulator](https://charticulator.com).
-## [Post-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/21)
+## [Post-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/21)
 
 ## Review & Self Study
 

3-Data-Visualization/12-visualization-relationships/README.md

@@ -10,7 +10,7 @@ This dataset of about 600 items displays honey production in many U.S. states. S
 
 It will be interesting to visualize the relationship between a given state's production per year and, for example, the price of honey in that state. Alternately, you could visualize the relationship between states' honey yield per colony. This year span covers the devastating 'CCD' or 'Colony Collapse Disorder' first seen in 2006 (http://npic.orst.edu/envir/ccd.html), so it is a poignant dataset to study. 🐝
 
-## [Pre-lecture quiz](https://purple-hill-04aebfb03.1.azurestaticapps.net/quiz/22)
+## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ds/quiz/22)
 
 In this lesson, you can use Seaborn, which you have used before, as a good library to visualize relationships between variables. Particularly interesting is the use of Seaborn's `relplot` function that allows scatter plots and line plots to quickly visualize '[statistical relationships](https://seaborn.pydata.org/tutorial/relational.html?highlight=relationships)', which allow the data scientist to better understand how variables relate to each other.