The application of machine learning continues to grow rapidly in a variety of industrial settings. In pharmaceutical development in particular, 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 goal of the Application of Machine Learning to Pharmaceutical Development Graduate Certificate program is to 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. In addition to covering a multitude of Machine Learning algorithms (generalized linear regression, non-linear regression, regularization methods, random-forest, neural networks, Markov processes, etc.), the program will emphasize the generation of contextualized visualization tools to adequately 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.
Who should consider this program?
The Application of Machine Learning to Pharmaceutical Development Graduate Certificate program is designed for students in the following programs who wish to pursue a career in pharmaceutical or related industries (chemical, food, etc.):
- chemical engineering
- mechanical engineering
- industrial engineering
- material science
- civil engineering
- environmental engineering