The purpose of this course is to learn about
data as a foundation for data science.
It might seem obvious, but half of data science
is data, so as you can imagine, it’s really
important to have a thorough understanding
of data to be successful with data science.
This course was designed to provide you with
that foundational knowledge.
As an overview of this course:
First, we’ll learn about data.
We’ll learn what it is and why it’s important
for data science.
Next we’ll learn about the various types of
data we encounter in data science including
categorical and numerical data.
Then we’ll learn about data types and how
we represent and store various kinds of data
in a computer.
Next, we’ll learn about tabular data — tables
of data organized into rows and columns
that allow us to perform queries.
Finally, we’ll learn about the data life cycle.
We’ll learn about the journey of data as we
move from raw data to actionable insight.
There are no prerequisites for this course.
We will assume you are new to data, data science,
and computer programming
throughout this entire course.
In addition, you won’t need to install any
software on your computer
to complete this course.
We’ll keep everything in this course as simple
and easy to understand as possible.
All of the content for this course can be
found at the following URL.
This includes videos, slides, quizzes, exercises,
and more.
If you haven’t already done so, please visit
this webpage now
and bookmark it for future reference.
By the end of this course, you will understand
data in the context of data science.
You’ll understand data types, data structures,
tabular data, and the data life cycle.
This foundational knowledge will help you
to understand all of the concepts in the remaining
courses on data science.
Alright, we have a lot to cover in this course,
so let’s get started!