Machine Learning with Omics Data

Health research is increasingly turning to high-throughput molecular datasets (also known as ‘omic’ datasets) to discover novel biomarkers of disease risk and outcome. Unfortunately, the size and complexity of these datasets makes them difficult to manage and prone to many pitfalls. In this course, we introduce you to the latest approaches from data science for interpreting and extracting useful and reliable biomarkers from these challenging datasets.

Note: This course was previously titled Advanced Epigenetic Epidemiology

Dates 20 - 21 June 2024
Fee £440
Format Online
Audience Open to all applicants (prerequisites apply)

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This course aims provide an overview of the principles and methods of epidemiology and data science that are relevant to high-throughput multi-omic studies and provide students with the knowledge and skills necessary to design and utilize population-based multi-omic studies to gain insight and to derive robust biomarkers of exposures and health outcomes.

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It is an excellent course. The tutors are nice and professional and very responsive to the questions from students. The lectures cover a wide range of topics and have lots of examples from the tutors' and their colleagues' research work. In addition, R Cloud is very convenient and simple to use in the practicals.

Course feedback, May 2022

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Find out about the self-paced Materials & Recordings version of this course [UoB only].

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