Graduate Certificate in Application of Machine Learning to Pharmaceutical Development

Develop the skill set necessary to evaluate and apply the growing portfolio of algorithms from the open source ecosystem and deploy them in the appropriate context.

The application of machine learning continues to grow rapidly in a variety of industrial settings. In pharmaceutical development, machine learning methodologies have been adopted to accelerate process optimization and material characterization – a trend that is anticipated to rise with the increased rate of data digitization.

The Application of Machine Learning to Pharmaceutical Development Graduate Certificate program is designed to develop the skill set you need to evaluate and apply the growing portfolio of algorithms from the open source ecosystem and deploy them in the appropriate context. In addition to covering a multitude of machine learning algorithms such as generalized linear regression, non-linear regression, regularization methods, random-forest, neural networks, Markov processes, etc., the program emphasizes the generation of contextualized visualization tools to sufficiently present results to a wider, non-expert audience as well as health authorities – a key aspect of the successful implementation of machine learning in pharmaceutical development.