Merge branch 'microsoft:main' into nirmalya8

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

@@ -45,7 +45,7 @@ Since data is a pervasive concept, data science itself is also a broad field, to
 <dl>
 <dt>Databases</dt>
 <dd>
-The most obvious thing to consider is **how to store** the data, i.e. how to structure them in a way that allows faster processing. There are different types of databases that store structured and unstructured data, which [we will consider in our course](../../2-Working-With-Data/README.md).
+The most obvious thing to consider is **how to store** the data, i.e. how to structure them in a way that allows faster processing. There are different types of databases that store structured and unstructured data, which <a href="../../2-Working-With-Data/README.md">we will consider in our course</a>.
 </dd>
 <dt>Big Data</dt>
 <dd>
@@ -53,7 +53,7 @@ Often we need to store and process really large quantities of data with relative
 </dd>
 <dt>Machine Learning</dt>
 <dd>
-One of the ways to understand the data is to **build a model** that will be able to predict desired outcome. Being able to learn such models from data is the area studied in **machine learning**. You may want to have a look at our [Machine Learning for Beginners](https://github.com/microsoft/ML-For-Beginners/) Curriculum to get deeper into that field.
+One of the ways to understand the data is to **build a model** that will be able to predict desired outcome. Being able to learn such models from data is the area studied in **machine learning**. You may want to have a look at our <a href="https://aka.ms/ml-beginners">Machine Learning for Beginners</a> Curriculum to get deeper into that field.
 </dd>
 <dt>Artificial Intelligence</dt>
 <dd>
@@ -61,7 +61,7 @@ As machine learning, artificial intelligence also relies on data, and it involve
 </dd>
 <dt>Visualization</dt>
 <dd>
-Vast amounts of data are incomprehensible for a human being, but once we create useful visualizations - we can start making much more sense of data, and drawing some conclusions. Thus, it is important to know many ways to visualize information - something that we will cover in [Section 3](../../3-Data-Visualization/README.md) of our course. Related fields also include **Infographics**, and **Human-Computer Interaction** in general. 
+Vast amounts of data are incomprehensible for a human being, but once we create useful visualizations - we can start making much more sense of data, and drawing some conclusions. Thus, it is important to know many ways to visualize information - something that we will cover in <a href="../../3-Data-Visualization/README.md">Section 3</a> of our course. Related fields also include **Infographics**, and **Human-Computer Interaction** in general. 
 </dd>
 </dl>
 

3-Data-Visualization/11-visualization-proportions/translations/assignment.zh-cn.md

@@ -0,0 +1,11 @@
+# 在 Excel 中试试
+
+## 指示
+
+你知道在 Excel 中可以创建圆环图、饼图和华夫饼图吗？使用你选择的数据集，直接在 Excel 电子表格中创建这三种图表。
+
+## 评分表
+
+| 优秀                     | 一般                    | 需要改进               |
+| ----------------------- | ------------------------ | ---------------------- |
+| 在 Excel 中制作了三种图表 | 在 Excel 中制作了两种图表 | 在 Excel 中只制作了一种图表 |