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 Learners can apply for Financial Aid directly with Coursera to assist with the cost of accessing the full course and gaining a certificate for successfully completing the course
What You'll Learn
- Learn about different data types in biomedical and healthcare contexts
- Understand computational methods in stratified healthcare
- Comprehend precision medicine concepts
- Review successful case studies from field leaders
Prerequisites
- Basic familiarity with the topic and its common terminology
- Readiness to practice through applied exercises or case-based work
Instructors
Dr Areti Manataki
Teaching and Research Fellow
Dr Frances Wong
Data Science MOOC Project Lead