Learning Outcomes

Upon completion of the program, students will be able to:

• Apply fundamental principles of health data science, including statistical modeling, data management, and data manipulation, to identify patterns and gain actionable insight to address challenges in industry, life sciences, and healthcare.
• Design workflows and applications as solutions to complex challenges in healthcare delivery.
• Collaborate across teams and functions to define problems, identify appropriate data, analyze sufficiency, and create visualizations to support communication and decision-making.
• Communicate effectively about properties of computer coding, task workflows, databases, and issues with data, including sufficiency, representation, and distribution.
• Explain machine learning, algorithms, and ethical challenges they represent in context with data science and their impacts on society.
• Evaluate data integrity and sufficiency and critically question analytical methods and approaches to manipulation across large data sets.
• Describe critical insight derived from data.