The increased availability of digital data in the pharmaceutical industry has enabled the adoption of machine learning models to advance pharmaceutical development efforts.  In addition, the emergence of open source languages with extensive libraries of powerful algorithms has transformed the way in which data science is adopted and practiced in pharmaceutical development organizations. This class provides the students with an introduction to pharmaceutical development aimed at contextualizing the incorporation of data science methodologies acquired in mathematical foundation courses (see requirements below).  Industrial case studies in the public domain will be used as practice examples to demonstrate the incorporation of data science principles to industrially relevant applications.