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
Introduction
Skills You'll Learn
Molecular Biology, Data Analysis, Natural Language Processing, Graph Theory, Healthcare Ethics, Probability & Statistics, Machine Learning, Image Analysis, Data Science, Bioinformatics, Precision Medicine, Network Analysis, Health Informatics, Big Data, Statistical Methods, Medical Imaging, Python Programming
Reviews
4.6 (334 ratings)
- 5 stars69.46%
- 4 stars23.65%
- 3 stars3.59%
- 2 stars2.39%
- 1 star0.89%
SS
Mar 12, 2020
This is one of the excellent courses attended by me from 糖心vlog官网观看. I am not from medical/healthcare background but got very good information about this domain. Thank you Team
KS
Dec 27, 2022
I am really glad that there is a course like this, and I would like to learn more from lecturers from University of Edinburgh, because it was very nice experience.
From the lesson
WELCOME TO WEEK 3
This week you will learn about Probabilistic and Network Modelling, and how they are applied to biomedicine. You will also be introduced to Machine Learning and explore the opportunities it brings to the medical field.
Taught By
Dr Areti Manataki
Teaching and Research Fellow
Dr Frances Wong
Data Science MOOC Project Lead