Uploaded March 2020 | Updated September 2026, 1 week ago
This series of videos on YouTube follows the chapters of my award winning massive open online course (MOOC) on Coursera called Understanding Clinical Research (or UCR for short). Anyone can view it without having completed UCR, though. If you want to learn how to use the most popular programming language for data science, then this series of videos are for you.
Just an FYI. UCR is an intuitive exploration of healthcare statistics. While I have other technical courses on Coursera, I wanted to add this companion to UCR on YouTube, to teach you how to use Python to do your own statistics and research.
In this video, I introduce you to the Python programming language. It's like learning a new spoken language. We don't learn a new language by studying a dictionary. We have to use the language. That is what we will ultimately be doing. There are a few fundamentals, though, that I need to show you. You don't need to memorize of even fully understand any of this video. It is just an introduction. So open a new Google Colab notebook and play some typing karaoke.
We will be using Google Colab. It is part of your free Google account, just as Google Docs. Simply log in to your Google account and go to https://research.colab.com. Click on WELCOME TO COLABORATORY and then on COPY TO DRIVE and Colab will be available in your Google Drive.
Colab allows us to create rich documents that look like Word documents. In between normal titles, subtitles, and paragraphs of text, we can also write Python code. This code will do all of our statistical analysis and create beautiful graphs. It's that simple. Python is the leading language for data science for good reason. It is easy to learn, yet so powerful. It is also FREE. No big name costs (I'm talking to you IBM SPSS). Using Python in Google Colab also means you have nothing to install. Later, though, I will show you how to install Python on your local machine. When working with sensitive patient data, it is good to follow local guidelines.
BTW, leave a comment down below if anything is unclear. There are nearly 100,000 students that have been a part of my Coursera course. We are a big community.
You can also jump ahead and get a certificate from my Research Unit at the University of Cape Town by completing the Biostatistics Fundamentals course on Udemy: udemy.com/course/biostatistics-fundamentals-using-python
If you want to take a look at UCR, you can click here: coursera.org/learn/clinical-research
This series of videos on YouTube follows the chapters of my award winning massive open online course (MOOC) on Coursera called Understanding Clinical Research (or UCR for short). Anyone can view it without having completed UCR, though. If you want to learn how to use the most popular programming language for data science, then this series of videos are for you.
Just an FYI. UCR is an intuitive exploration of healthcare statistics. While I have other technical courses on Coursera, I wanted to add this companion to UCR on YouTube, to teach you how to use Python to do your own statistics and research.
In this video, I introduce you to the Python programming language. It's like learning a new spoken language. We don't learn a new language by studying a dictionary. We have to use the language. That is what we will ultimately be doing. There are a few fundamentals, though, that I need to show you. You don't need to memorize of even fully understand any of this video. It is just an introduction. So open a new Google Colab notebook and play some typing karaoke.
We will be using Google Colab. It is part of your free Google account, just as Google Docs. Simply log in to your Google account and go to https://research.colab.com. Click on WELCOME TO COLABORATORY and then on COPY TO DRIVE and Colab will be available in your Google Drive.
Colab allows us to create rich documents that look like Word documents. In between normal titles, subtitles, and paragraphs of text, we can also write Python code. This code will do all of our statistical analysis and create beautiful graphs. It's that simple. Python is the leading language for data science for good reason. It is easy to learn, yet so powerful. It is also FREE. No big name costs (I'm talking to you IBM SPSS). Using Python in Google Colab also means you have nothing to install. Later, though, I will show you how to install Python on your local machine. When working with sensitive patient data, it is good to follow local guidelines.
BTW, leave a comment down below if anything is unclear. There are nearly 100,000 students that have been a part of my Coursera course. We are a big community.
You can also jump ahead and get a certificate from my Research Unit at the University of Cape Town by completing the Biostatistics Fundamentals course on Udemy: udemy.com/course/biostatistics-fundamentals-using-python
If you want to take a look at UCR, you can click here: coursera.org/learn/clinical-research
