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Students will analyze and evaluate various aspects of health analytics and big data analytics. Topics covered include descriptive, predictive and prescriptive analytics, translating healthcare problems as an analytics problem, and the use of natural language processing to gain insights from electronic health records and other open text formats.

The students will be able to:• Develop techniques and processes for data-driven decision-making.• Build, verify and test predictive data models.• Analyze patterns in large amounts of data in information systems and how to use these to draw conclusions.• Design and develop modeling solutions for clinical decision-making.• Discover how to answer strategic and operational questions using basic analytic techniques.• Analyze and compare metadata and its importance within an organization, and data extraction technologies.• Apply natural language processing concepts to gain insight into electronic records and other open text formats• Practice individual investigations in chosen topics.

*The learning goals displayed here are those for one section of this course as offered in a recent semester, and are provided for the purpose of information only. The exact learning goals for each course section in a specific semester will be stated on the syllabus distributed at the start of the semester, and may differ in wording and emphasis from those shown here.