Courses:
GPH-GU 2501 Special Topics: Data Science and Machine Learning in Public Health Practice and Research
This short course will introduce and encourage thinking around new datasets and methods in epidemiology and public health. The data science pipeline, across data gathering, processing, analysis and communication will be covered. Content will include summaries of current and best practices from the literature, discussion of research papers and methods in terms of their appropriateness in public health, and approaches to address methodological challenges. Content will relate to both infectious diseases such as COVID-19 and non-communicable diseases. Students are encouraged to bring their own dataset or use publicly available ones to develop their own data science project, and time will be allotted for discussing project challenges.
CS-GY 9223 Foundations of Data Science
This course introduces students to methods in applied data science. The class is approached from a problem-based perspective, emphasizing the select ion and evaluation of methodology appropriate to real-world problems. Students will learn statistical and computational methods for working with data.
UGPH-GU 20 Biostatistics for Public Health
This course introduces basic concepts and techniques in the analysis of public health data. It is an applied course, emphasizing use, interpretation and limits of statistical analysis. Real world examples are used as illustrations, and computer-based data analysis is integrated into the course. My section will learn to use the programming language R — a great professional opportunity for public health students, and students have responded with positive feedback on this experience!