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
シラバス - 本コースの学習内容
Welcome to the Course
Join us this week to find out how the course works and to try your hand at programming in Python!
WELCOME TO WEEK 2
This week you will be introduced to Sequence Processing and Medical Image Analysis. Explore the course materials to find out about recent advances in these areas and how they contribute to Precision Medicine!
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.
WELCOME TO WEEK 4
This week you will discover how clinical notes and other free-form text can be analysed with the use of Natural Language Processing techniques. You will also find out how Process Modelling can help us understand, stratify and improve healthcare processes.
20%
14%
Data Science in Stratified Healthcare and Precision Medicine からの人気レビュー
Great course, really well designed and well produced and I feel like I've learned a lot! The coding was a bit of a shock to the system but it was nice and challenging. Thank you to the team!
An excellent introduction to Data Science in healthcare!\n\nOverall, this course was very knowledgeable, interactive, challenging and fun!\n\nThank you Coursera!
講師
Dr Areti Manataki
Teaching and Research Fellow
Dr Frances Wong
Data Science MOOC Project Leadエディンバラ大学（The University of Edinburgh）について
よくある質問
いつ講座や課題にアクセスできるようになりますか？
修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題（該当する場合）にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。
修了証を購入すると何を行えるようになりますか？
修了証を購入する際、コースのすべての教材（採点課題を含む）にアクセスできます。コースを完了すると、電子修了証が成果のページに追加されます。そこから修了証を印刷したり、LinkedInのプロフィールに追加したりできます。コースの内容の閲覧のみを希望する場合は、無料でコースを聴講できます。
返金ポリシーについて教えてください。
学資援助はありますか？
さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。
