Basic Science Research Track,
Clinical Research Training Program
Duke University School of Medicine
Course Director: Matthew Engelhard
This site is intended to accompany the main course site in Talent LMS
- Please review the syllabus by clicking here
- Materials for each week are linked in the schedule in Talent LMS
- A weekly reading + survey will be due before each class (with exceptions noted in Talent LMS)
- Readings are linked below, and surveys must be completed in Talent LMS
- Both are pass/fail and together are a substantial portion (20%) of your final grade
- Weekly computational exercises will be due before class (again with a few exceptions, as noted in Talent LMS)
- Each exercise will present code and output, then ask you to modify the code to complete additional tasks
- These exercises require you to code in Python in a Jupyter Notebook environment
- We recommend either installing Anaconda or working in Google Colab.
- Recommended Python resources include Duke Library tutorials, Python Crash Course, and Google Python class
- The course will culminate in a project in which you apply data science methods to a clinical dataset of your choosing.
- Project instructions and grading details are here.
- Proposals are due before class in week 6, and the project is due before the final class period.
- Please follow the schedule and activities posted in Talent LMS