Machine Learning for Metabolomics

Overview

What you will learn

On successful completion of this Machine Learning for Metabolomics course offered by Cranfield University you will be able to:

• Critically assess various metabolomics analytical and spectral platforms,

• Apply state-of-the-art best practices in machine learning to fit the purpose of the analysis,

• Critically understand the basic principles of the most common instrumental techniques used in metabolomics, the technical limitations and the underlying biological and experimental assumptions that impact on data quality,

• Demonstrate in-depth knowledge of the current approaches for modelling and warehousing of life science data,

• Develop classification and regression models based on multivariate metabolic data,

• Evidence an In-depth understand and application of machine learning algorithms and be able to provide examples of specific machine learning algorithms for each task,

• Apply statistical and machine learning procedures covered during the module, to derive biological relevant information from metabolic datasets using R.