Courses

Exploratory Data Analysis for Health [LHS 601]

This course introduces students to fundamental skills needed to explore health data. The course focuses on two large themes: (a) exploring health data in the context of the US healthcare system using the statistical programming language R, and (b) evaluating the potential role of machine learning to support health-related decisions. Learning from health data requires a solid grasp of data operations, data visualization, statistics, and machine learning, as well as an understanding of ethical and legal frameworks guiding health data privacy and security. The course focuses on giving students an introductory understanding of health data and its limitations, while developing knowledge, skills, tools, and techniques that are critical for data analysis. Special emphasis is placed on learning a tidyverse-based approach, which is a popular data analysis framework in R.

Course syllabus [pdf]

Updated: 01/19/2024

Quality Improvement in Healthcare Systems [LHS 641]

This course addresses quality improvement (QI) in healthcare using a multi-level systems perspective. The course addresses both conceptual foundations of QI and direct application of QI tools and processes. Course materials include examples and application at Michigan Medicine. The course will help participants perform successful QI activities in healthcare settings.

Course syllabus [pdf]

Updated: 01/05/2023

Learning Analytics [SIADS 680]

SAIDS 680 provides an overview of a key application domain for data scientists—education. Anchored in the fields of learning analytics (LA) and educational data mining (EDM), this course analyzes the unique opportunities and challenges associated with applying data science methods to data stemming from schools, universities, and a myriad of learning opportunities. The course covers the history of learning analytics, typical data and methods used, the importance of measurement, and the implementation of learning analytics products.

Course syllabus [pdf]

Updated: 08/01/2022

Learning Analytics: Foundations and Applications [LHS 631]

Learning analytics involves collecting, analyzing, and communicating with data about learners and learning environments. This course addresses efforts to use new and novel data sources as well as diverse analytical techniques to improve learning opportunities in K-16 and professional settings (e.g., healthcare). This class is intended for students who are broadly interested in learning, whether that learning takes place in the classroom, in the home, or on the shop floor.

Course syllabus [pdf]

Updated: 08/10/2021