COURSE CURRICULUM

Health Analytics consists of 60 credits and is structured across four semesters to provide students with a comprehensive education in health data science. In the first semester, students establish core skills through courses such as Data Wrangling and Visualization, Mathematics Computation, Health Care Analytics, Elementary Applied Statistics, and Calculus and Linear Algebra with Business Applications. The second semester deepens analytical capabilities with Machine Learning I, Comparative Health Systems, Management Information Systems, Mathematics for Machine Learning, and an elective in Discrete Structures for Data Science or Introduction to Discrete Structures. In the third semester, students advance their knowledge with Machine Learning II, Health Care Information Systems, Regression Analysis, Encryption Algorithms for Data Protection, and one elective course. The final semester emphasizes integration and application through courses like Epidemiology and Health Analytics, Dashboards and Analytic Reporting, Modern Statistical Methods, and a capstone Data Science Project. Another elective course is also included in the final term. This curriculum ensures that students are equipped to handle large-scale data challenges in healthcare settings by applying advanced statistical and machine learning techniques, understanding information systems and data privacy, and developing data visualization and communication skills necessary for effective decision-making in health analytics.