@ -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 <ahref="../../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 <ahref="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 <ahref="../../3-Data-Visualization/README.md">Section 3</a> of our course. Related fields also include **Infographics**, and **Human-Computer Interaction** in general.