Learning Outcomes

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

• Apply fundamental principles of 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 organizational challenges.
• 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 distributions.
• 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 large data sets.