Data Science School: Machine learning applications for life sciences (Online)
Organizer: University of Cambridge
Host institution: University of Cambridge Bioinformatics Training
Start: Thursday, 17 September 2020 @ 09:00
End: Tuesday, 22 September 2020 @ 12:30
Venue: Craik-Marshall Building
Country: United Kingdom
Postcode: CB2 3AR
Scientific topic: Machine learning, BioinformaticsTarget audience:
- Students and researchers from life-sciences or biomedical backgrounds
- who have
- or will shortly have
- the need to apply the techniques presented during the course to biomedical data.
- The course is open to Graduate students
- Postdocs and Staff members from the University of Cambridge
- Institutions and other external Institutions or individuals
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £400. </span style> <span style="color:#0000FF">All Members of the University of Cambridge to pay £200. </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>
THIS EVENT IS NOW FULLY BOOKED!
PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.
This School aims to familiarise biomedical students and researchers with principles of Data Science. Focusing on utilising machine learning algorithms to handle biomedical data, it will cover: effects of experimental design, data readiness, pipeline implementations, machine learning in Python, and related statistics, as well as Gaussian Process models.
Providing practical experience in the implementation of machine learning methods relevant to biomedical applications, including Gaussian processes, we will illustrate best practices that should be adopted in order to enable reproducibility in any data science application.
This event is sponsored by Cambridge Centre for Data-Driven Discovery (C2D3).
- Workshops and courses