HSMA Resources

Here we provide links to key resources, not only for current HSMAs and HSMA alumni, but for anyone anywhere in the world to use. All of our materials are made available Free and Open Source.

Watch our lectures

All of our past HSMA lectures (from HSMA 3 onwards) are available on our HSMA YouTube channel for you to watch or rewatch

Lectures from each round are sorted into individual playlists and given in lecture order. 

Access our training materials

All of our training materials are made available Free and Open Source, with most of the content provided under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International [cc-by-nc-sa] License, meaning you are welcome to copy, share and adapt most of our materials

The materials, including lecture slides, code examples, exercises and solutions, can be found on GitHub. 

HSMA GitHub
https://github.com/hsma-programme 

Download the software

The Python programming language
We currently recommend the Anaconda scientific package, which also includes Spyder and Jupyter Lab IDEs : https://docs.anaconda.com/anaconda/navigator 

QGIS Version 3
https://qgis.org/en/site 

Quarto 

Access online at: https://quarto.org/docs/get-started/
You will need to download and run the appropriate installer from the page above for your operating system.

VSCode
VSCode is available for Windows, Linux and Mac Operating Systems, and is available here : https://code.visualstudio.com/Download

Zoom
https://zoom.us 

Slack
https://slack.com/intl/en-gb
You will receive an invite to the Slack workspace as a current or previous HSMA. If you do not have an invite, please contact the HSMA Programme Lead.

InsightMaker
https://insightmaker.com 

Google CoLaboratory
https://colab.research.google.com 

Git version control software
This should already be installed if you are using Linux but see below for how to check:


Find out more

Titanic Survival Machine Learning
Dr Mike Allen (PenARC) has a fantastic website dedicated to teaching people concepts in Machine Learning, from the basics all the way through to advanced cutting-edge concepts, using Kaggle’s Titanic Survival data: 

R for healthcare
Dr Sean Manzi has a brilliant and comprehensive resource for those wishing to learn how to use the R language for healthcare analytics, with lots of examples relevant to routine analytical tasks that have been traditionally undertaken in other software, such as Excel.

Python for Health Data Science
Prof Tom Monks (PenARC) has an excellent online textbook for learning sufficient Python to be a “credible data scientist”.

Towards Data Science
A great resource that collates contributions from independent data science authors on a wide variety of topics.

Stack Overflow
One of the world’s most popular communities helping people develop their coding expertise.

Keep up-to-date with our research and find out more: