This course covers the main aspects related to the analysis of the metabolic profile in living organisms and explores statistical and computational techniques that are central to the field of metabolomics with particular emphasis to machine learning.

Machine learning is a rapidly expanding form of artificial intelligence (AI) which has found many applications in the field of metabolomics. Examples include explanatory analysis of complex biological systems, novel biomarker discover and prediction modelling.

At a glance

  • DurationFive days
  • LocationCranfield campus
  • Cost


What you will learn

On successful completion of this course 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.

Core content

  • Metabolomics: overview and workflow,
  • Multivariate classification and biomarker discovery,
  • Introduction to machine learning,
  • Applications of machine learning in metabolomics,
  • Advanced topics in machine learning,
  • Applications of machine learning in food metabolomics,
  • Advanced topics in R.

Upgrade to a professional qualification

Cranfield credits are available for this short course which you can put towards selected Cranfield degrees. Find out more about short course credit points.

Accommodation options and prices

This is a non-residential course. If you would like to book accommodation on campus, please contact Mitchell Hall or Cranfield Management Development Centre directly. Further information regarding our accommodation on campus can be found here.

Alternatively you may wish to make your own arrangements at a nearby hotel.

Location and travel

Cranfield University is situated in Bedfordshire close to the border with Buckinghamshire. The University is located almost midway between the towns of Bedford and Milton Keynes and is conveniently situated between junctions 13 and 14 of the M1.

London Luton, Stansted and Heathrow airports are 30, 90 and 90 minutes respectively by car, offering superb connections to and from just about anywhere in the world. 

For further location and travel details

Location address

Cranfield University
College Road
MK43 0AL

Read our Professional development (CPD) booking conditions.