This course is suitable for PGR students in the Medical School with limited/no experience in programming and is tailored to the use case of biomedical research. The objective is that after this course, the students can have a basic idea of the key elements for conducting a biomedical data science project, including
- Basic Python programming skills
- Querying data through web service
- Processing the data
- What can machine learning do in biomedical research and basic practice
We will include examples from biomedical research and hands-on exercises using existing biomedical datasets (e.g., breast cancer Wisconsin dataset, and the WHO COVID-19 dataset).
Materials for the training will be added before the course.
- Zhaozhen Xu, zhaozhen.xu [at] bristol.ac.uk
- Yi Liu, yi6240.liu [at] bristol.ac.uk
- Weili Qiu, w.qiu [at] bristol.ac.uk
Please ensure you read the pre-course-installation-guide to setup the Python environment before the course.
If you have any question, we will have a drop-in session from 13:00 to 14:00 at OS6 (2nd floor), Oakfield House, BS8 2BN.
For a day in Python 101, we will cover basic elements of the Python programming language, including variables, data structures, control structures, functions, etc. We will also introduce tools for running code in Python, such as the Jupyter Notebook environment and the Visual Studio Code text editor.
We will go through the process of working with a data source, starting by getting the data from an external source (e.g., the WHO COVID-19 dataset). Then, we will introduce some libraries (e.g. Numpy, Pandas, Matplotlib) for handling and visualising the data.
We will introduce machine learning and large language models and give some examples of their application in biomedical research. As machine learning is a broad topic, we would like to give some basic ideas about it in this one-day tutorial so the students can explore it further in their future research.