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Through class discussion and interactive Python data exercises, this course provides practical experience working with electronic medical record data. The class will provide students access th the Johns Hopkins Precision Medicine Analytics Platform (PMAP) to conduct analysis on a de-identified EMR dataset of 60K patients with over 100 million data elements. The class will work with Jupyter notebooks to learn how to prepare EMR data and contruct models from encounter, symptoms, lab, procedure, vitals and medication data. The topics will include exploratory data analysis,data cleaning, feature extraction, model construction, and evaluation. Working knowledge of SQL is expected and Python encouraged. The class will have access to the PMAP cookbook of Jupyter notebook recipes and Datacamp accounts will be provided for students to master working with major Python librairies Pandas, Matplotlib, Numpy and Sci-kit.