Coding and Data Analysis in Biomedicine (BIOL90042)

In this subject, students will develop and demonstrate a comprehensive understanding of how to use computer code to analyse, visualise, model and make evidence-based decisions from large data sets. Through the development of a solid understanding of the theory and practice of data science for biomedical research, students will gain the necessary knowledge to identify and evaluate suitable data analysis tools for application in biomedical and clinical data sets via coding tutorials utilizing AI co-piloting models. Lectures will cover data visualization and visual communication, core statistical concepts including machine learning methods, and their application in the analysis of biomolecular data and health informatics. 

This subject will be delivered through online lectures that delve into the principles of data analysis and AI, and its practical implementation in biomedical research. To enhance the learning experience, students will gain valuable practical training in the R software language that will teach them reproducible and transparent data science practices and responsible use of AI assistance whilst building foundational skills in data analysis and visualization, basic statistical analysis, report generation and process automation. Students will learn to perform analysis on datasets pertaining to bioinformatics and disease, and communicate findings through code-based (markdown) reports and oral presentations.