À propos de ce cours : 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
Les destinataires de ce cours : 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.
Créé par : Université d'Édimbourg
Enseigné par : Dr Areti Manataki, Teaching and Research Fellow
Centre for Medical Informatics
Enseigné par : Dr Frances Wong, Data Science MOOC Project Lead
College of Science and Engineering
| Niveau | Intermediate |
| Engagement | 5 weeks of study, 3-4 hours/week |
| Langue | English |
| Comment réussir | Réussissez tous les devoirs notés pour terminer le cours. |
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Université d'Édimbourg
Influencing the world since 1583, The University of Edinburgh is consistently ranked as one of the world's top 50 universities. Today, we are an established and global leader in online learning, providing degree-level education to 3,000 online students in addition to 36,000 students on-campus. We also offer a wide range of free online courses in a variety of subjects. To find out more about studying for one of our online degrees, search for ‘Edinburgh online’ or visit www.ed.ac.uk
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