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Biomedical Data Science for Master’s Students

The past decade has seen major advances in our ability to acquire data on human health across multiple spatio-temporal scales. This wealth of data poses challenges that have never before been confronted. At the heart of these is understanding how massive biomedical data sets are best analyzed to discover new knowledge about the function of living systems in health and disease, and how this knowledge can be harnessed to provide improved, more affordable health care. Because of their deep and broad cross-training in biology, medicine, and engineering, Johns Hopkins biomedical engineers are ideally positioned to take on this challenge.

The Biomedical Data Science focus area provides an educational curriculum that trains students in how to solve such problems. This training is done in close collaboration with faculty of the Departments of Anesthesiology & Critical Care Medicine, Neurology, Neurosurgery, and Psychiatry. We are creating a common research and teaching space where students and faculty of these departments work together with biomedical engineers to develop novel cloud-based technologies and data analysis methods that are needed to improve our ability to diagnose and treat disease more effectively while reducing costs.

Below, you will find a suggested list of courses to help you in your course planning. Your academic interests determine the remaining courses (focus area electives). You will meet with the faculty lead of your chosen focus area to determine your course plan. The program administrator will provide additional advisement and course approval. Please note that all listed courses are suggested and may not always be offered. Course offerings are subject to change from semester-to-semester.

A group of students and faculty chat while working around a laptop.
BDS Focus Area Courses
  • Biomedical Data Design I (EN.580.697)
  • Biomedical Data Design II (EN.580.638)
  • Precision Care Medicine (EN.580.680/681)
  • Spring (3rd and 4th terms through the School of Public Health) – You must register for both:
    • Data Science for Public Health I (PH.140.628.71)
    • Data Science for Public Health II (PH.140.629.71)
    • *Instructor and advisor approvals required with the submission of an interdivisional registration form through SEAM
BDS Focus Area Electives
  • Computational Molecular Medicine (EN.553.650)
  • Data Mining (EN.553.636)
  • Foundations of Computational Biology and Bioinformatics II (EN.580.688)
  • High Dimensional Approximation, Probability, and Statistical Learning (EN.553.738)
  • Introduction to Probability (EN.553.620)
  • Introduction to Statistics (EN.553.630)
  • Machine Learning (EN.601.675)
  • Machine Learning: Data to Models (EN.601.676)
  • Machine Learning: Deep Learning (EN.601.682)
  • Mathematical Foundations of Biomedical Engineering I (EN.580.704)
  • Biomedical Data Design I (EN.580.697)
  • Biomedical Data Design II (EN.580.638)
  • Precision Care Medicine (EN.580.680/681)
  • Sparse Representations in Computer Vision and Machine Learning (EN.580.709)
  • Statistical Machine Learning (EN.601.775)
  • Statistical Theory (EN.553.730)
  • Unsupervised Learning: From Big Data to Low Dimensional Representations (EN.600.692)

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