Data Analytics for Biomedical Applications
About This Course
This course in biomedical data analytics focusses on statistical analysis, machine learning, and advanced data visualisation. Learners will leverage Python and cutting-edge analytical software to interpret complex biomedical and healthcare datasets, including genomics and medical imaging. Through hands-on sessions, learners will develop skills in predictive modeling, personalised medicine, and clinical research. This micro-credential course also emphasises ethical practices and data-driven decision-making, preparing learners for professional opportunities in bioengineering and biomedical research work, which is ideal for those pursuing or advancing their industrial careers in biomedical engineering roles.
As this micro-credential course is only offered in the FlexiMasters in Biomedical Engineering Principles and Practices programme, learners are required to enrol in and complete all required courses within this programme.
What You'll Learn
1. Apply statistical, machine learning and data visualisation techniques to analyse complex biomedical datasets, such genomic data and medical imaging.
2. Utilise programming languages like Python, alongside state-of-the-art software, to solve real-world biomedical challenges effectively.
3. Evaluate ethical considerations in biomedical data analytics and demonstrate readiness for advanced research or professional roles in the field.
4. Integrate bioengineering and data analytics knowledge to address key challenges in personalised medicine and clinical research.
Entry Requirements
No pre-requisites are needed to enrol in the course; however, learners without qualifications or work experience in relevant engineering or the related fields may find the course contents challenging.
Note: Shortlisting will be conducted.