Data Science in Clinical Research Track
Data science in clinical research is an emerging discipline in response to the explosion of available and complex data in biomedicine and related streams.
This program approaches data science as an interdisciplinary field, blending informatics, computer science, biostatistics and epidemiology. It provides broad background and expertise in accessing and manipulating data and forming inferences from data.
Coursework in the data science track extends upon MAS program’s foundation of epidemiology and biostatistics to include required and elective courses in advanced data manipulation, prediction, clustering/pattern recognition and data reduction.
The data science track of the MAS program distinguishes itself from other data science training programs by providing a solid base of epidemiology and clinical research in the context of human subjects-based health research. Graduates of the data science in clinical research track are prepared to work in academia, industry, or municipal health systems.
Scholars completing this track may list "Master of Advanced Studies, Clinical Research with Specialization in Data Science" on their curriculum vitae.
Please contact John Kornak, PhD with any questions.
Apply to this program by May 31, 2020.
Sample Course Schedule
Year 2 | ||
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Fall | Winter | Spring |
BIOSTAT 210 — Biostatistics for Clinical Research IV (2) EPI 221 — Master's Seminar II (1) Machine Learning in R |