Health Data Analytics MOOC (CSS)

This course is designed to provide participants with a detailed description of data analytics in health care. Big data in health care has sparked a lot of interest in applying large-scale data analytical techniques for acquiring new information about existing data. In order to become proficient in data analytics one must first understand the foundational component of how the data is stored and acquired. Therefore, the first part of the course will focus on database design and executing structured query language (SQL) scripts in MySQL workbench for acquiring data. Once the data is in hand, the next step is to analyze that data. Commonly, statistical techniques are utilized for testing hypothesis and determining if there are statistically significant observations. However, with the expansion of big data there is an opportunity to move away from hypothesis testing and acquire new knowledge using data mining modeling. In this course, statistical analyses and data mining techniques will be discussed along with methods for deploying these techniques using the open-access analytical software, R. After taking this course, you will have a better understanding of the nature of big data and the methods used for acquiring, analyzing, and ultimately discovering new information from data.

Upon completion of the course students will be able to:

• Describe the opportunities and challenges with big data
• Design a database and execute SQL scripts for querying the data
• Apply basic statistical and data mining procedures to health care data.
• Utilize the program R for statistical and data mining purposes.

The courses starts at October 14, 2013. Students can register until November 11, 2013.
The course is self-paced and is designed to be completed in eight weeks and represents the equivalent of 2 credits, however, because this course is free no credit will be granted.

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