About this course: An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine. You will have a hands-on experience of working with such data. And you will learn from leaders in the field about successful case studies. Topics include: (i) Sequence Processing, (ii) Image Analysis, (iii) Network Modelling, (iv) Probabilistic Modelling, (v) Machine Learning, (vi) Natural Language Processing, (vii) Process Modelling and (viii) Graph Data. Watch the course promo video here: http://edin.ac/2pn350P
Who is this class for: This course is aimed at learners who are familiar with the basic principles of biomedical and healthcare practice, and who have an interest in data science. Prior knowledge in computer programming or data science is not needed.
Created by: The University of Edinburgh
Taught by: Dr Areti Manataki, Teaching and Research Fellow
Centre for Medical Informatics
Taught by: Dr Frances Wong, Data Science MOOC Project Lead
College of Science and Engineering
| Level | Intermediate |
| Commitment | 5 weeks of study, 3-4 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
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