Data analytics plays an increasingly greater role in healthcare organizations. However, many healthcare professionals lack training in this vital area. This course will cover advanced data analytics with applications in healthcare systems engineering. In specific, the course will cover the concepts and methods of the data analytics in three particular areas: (i) descriptive analytics, which includes data description and aggregation; (ii) predictive analytics, which uses machine learning and statistical modeling for prediction and forecasting; and (iii) prescriptive analytics, which makes use of the results of predictive analysis to optimize the decision making process. All introduced methods will be demonstrated along with a variety of data modalities collected from healthcare applications such as pervasive health, disease diagnosis, fraud detection, and pharmaceutical discovery along with medical decision support systems. Through the provided coursework, students will be able to learn a variety of methodologies on data processing and modeling and make the best use of healthcare data to facilitate medical decision making. Prerequisites: SSIE 437/537: Industrial and Systems Engineering in Healthcare or permission from the instructor. 3 credits.