Course List (3 courses, 10 units)
The Certificate in Leadership and Strategy in Healthcare Analytics is one of three stackable certificates that make up the Master of Science in Healthcare Data Analytics program. It can be completed as a standalone certificate* for targeted professional development or applied toward the master’s degree.
*Please review the Admission Requirements for this certificate.
Certificate 3: Leadership and Strategy in Healthcare Analytics (10 Units)
- MHDA 503: Leadership and Ethics in Healthcare Data Analytics (3 units)
- MHDA 507: Statistical Analysis for Health Analytics (3 units)
- MHDA 509: Machine Learning and Artificial Intelligence in Healthcare (4 units)
| Course | Name | Units | Description |
|---|---|---|---|
| Certificate 3: Leadership and Strategy in Healthcare Analytics (can be taken as part of the master’s degree or individually) | |||
| MHDA 503 | Leadership and Ethics in Healthcare Data Analytics | 3 units | This course is designed to provide a solid foundation in leadership and ethical decision making with relation to management of Healthcare Data Analytics strategies and functions. Related theoretical concepts are reviewed, and practical applications are emphasized. |
| MHDA 507 | Statistical Analysis for Health Analytics | 3 units | This course offers a comprehensive exploration of statistical methods used in healthcare analytics. Specifically designed to meet the needs of the healthcare industry, the course focuses on various statistical techniques, including descriptive, inferential, and multivariate statistics. Students will learn to apply these methods to healthcare data, enhancing their skills in predictive modeling and advanced experimental design. The course also covers power analysis and survival analysis, equipping students with a robust understanding of these essential concepts in healthcare analytics. |
| MHDA 509 | Machine Learning and Artificial Intelligence in Healthcare | 4 units | This course provides an overview of how artificial intelligence is transforming the healthcare industry. Students will gain hands-on experience applying artificial intelligence and machine-learning techniques to real-world healthcare challenges. Topics covered include data wrangling and cleaning data, linear and logistic regression, decision trees, and popular models in use for machine learning. Students will gain insights on how to deploy big data architectures and why they are essential and used in healthcare and other industries. |
