Biomedical Data Science Bootcamp, Part 2: Introduction to Python for Biomedical Data Science

July 5-7, 2017 
(Instructor: Brian Chapman)

Prerequisites: Biomedical Data Science Bootcamp, Part 1: Computing Environments

Using case-based learning, students will learn foundational biomedical data science skills by creating Python computer programs that address biological and health-care case studies. Cases will be analyzed in terms of what data are generated and consumed and how that data can be represented, visualized, and analyzed so as to address the biological or health care challenge. Starting with foundational programming concepts (data types, data structures, logic control) students will build up to writing Python programs to analyze a variety of biomedical data types including numeric measurements, time series data, textual data, and graph data. Focus will be on using high level Python tools such as Pandas, Biopython, and NetworkX.

Learning Objectives

  1. Students will use Pandas to read, write, and analyze numeric, genomic, and textual data
  2. Students will learn how to use APIs to retrieve data through remote resources
  3. Students will execute SQL queries through Python to retrieve data from relational databases