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BMI 6319 Data Analysis for Scientific Research in Biomedical Informatics

3 semester credit hours
Lecture contact hours: 2; Lab contact hours: 3
Web-based and classroom instruction
Prerequisites: BMI 5007 or consent of instructor
Required for PhD students
Lab Fee: $30

This is a PhD level course which will expose students to the best practices in Health Data Science in biomedicine and healthcare. The students will devise a plan for a reproducible data analysis pipeline which will be developed throughout the course. The course will involve class discussions and sharing of ideas on methodologies and Health Data Science tools, with particular emphasis on reproducibility. The data analysis plan, including choice of dataset, will be student driven but it will require approval from the students’ PhD supervisor and the course instructor.

Upon successful completion of the course, students will:

  • Plan a reproducible data analysis pipeline
  • Select and utilize modern Health Data Science tools to generate the planned analysis


  • Current enrollment in doctoral program
  • Ongoing project involving data analysis and access to the dataset to be analyzed
  • While your specific data analysis might leverage different software packages and programming languages, you will be required to have working knowledge of Python.