Massv Health Data Fundamentals

3 Credits · Level: Graduate

This basic course is a broad overview of how data analytics is used in healthcare and medical research settings. Here, we primarily focus on the use of a data analytic framework to advance the goals of healthcare, research and product development organizations. We attempt to cover the people, process, infrastructure needs, tools, skills, organization and governance to effectively perform this work in a healthcare organization or an organization that is in the ecosystem of a healthcare system. We do not focus on any particular quantitative methodologies. Here we provide a broad overview of the field with exposure to several common tools, software packages, usecases with a focus on hands-on problem solving. There is a parallel lab portion of this course that covers the various types of healthcare related big data (EHR, Claims, population health, patient registries, social media etc) and health IT tools to manage and analyze them. This is a hands-on, practical portion of the course about using informatics methodologies and tools and cloud computing resources to do analysis and manipulation of datasets that are too large to fit on a single machine and/or analyzed with traditional tools. The lab portion of the course will focus on Pandas, MatPlotLib, autoML, NLP libraries, Spark, MapReduce, the Hadoop Ecosystem and other tools. You will understand how to acquire and/or ingest the data, and then massage, clean, transform, analyze, and model it within the context of Big data analytics. You will be able to think more programmatically and logically about your Big data needs, tools and issues.