3 semester credit hours
Lecture contact hours: 2; Lab contact hours: 3
Web-based and classroom instruction
Prerequisites: consent of instructor
Lab Fee: $30
This course will expose students to 'Big Data' projects in biomedicine and healthcare. Through real-world examples we will explore the challenges and success faced by initiatives to improve health care delivery through big data projects. Specific topics may include but are not limited to the Vs of Big Data (volume, velocity, variety, veracity, and value), data analytics, accountable care organizations and population health management.
Upon successfully completing this course, students will:
These objectives will be pursued by hands-on examples using Python-based data analysis libraries such as Pandas and PySpark. We will be using modern container technologies (Docker) and databases built to store “Big Data.”