Healthcare Data Analytics - MS

The Master of Science in Data Analytics will prepare you to play a valuable role in data science and analytics in the healthcare sector with a strong foundation in the following areas:

  • Data analytics fundamentals: Learn about data analysis tools and techniques, such as python programming, data visualization, and statistical analysis, as well as understanding how to clean, organize, and manipulate data sets.
  • Technical aspects of understanding data: This may include learning about different types of data, such as structured and unstructured data, and how to identify and handle missing or incomplete data.
  • Creating models to tell a useful story: Learn about different types of models, such as regression, classification, and clustering, and how to select and apply the appropriate model for a given problem. And, be able to communicate the results of your analysis effectively to different stakeholders.
  • Driving outcomes and change in healthcare settings: This involves learning about the challenges and opportunities presented by data analytics in the healthcare sector, as well as understanding how to apply data analytics to address specific problems and improve patient care. Learn about the ethical and legal considerations related to the use of healthcare data.

Note: Spring admittance to the MSDA Program will be considered for students who present with prior experience and coursework relevant to the content and skills taught in Dynamic Healthcare Data Analytics Techniques & Methods: DA-620 and DA-720 for the 12-month or 24-month MSDA curricula. Review of requested information will be conducted by the appropriate course instructor and Program Director.