Introduction to Health Data Science: Applied Machine learning and statistical learning in Epidemiology

3 credits · Graduate

Health data science refers to analysis of large volumes of complex data using statistical learning and machine learning approaches. The course is designed to deliver in two parts. First part covers descriptive data summery and visual displays of big data. Second part guides students through analytical steps of numerical and textual data analytical tools. Focus will be on basic applied machine learning techniques, text using RapidMiner software and statistical learning on numerical data mining, data visualization, pattern recognition and predictive analytics using R software. PREREQUISITES: Elementary statistics equivalent to CHE5019 and/or biostatistical modeling CHE 6019 or equivalent course. FORMATS: Lecture | Seminar | Discussion