|Course ID||Course Name||Instructor||Semester||Time | Day|
|HGEN 611||Data Science I||Timothy York||Fall||10:30-11:50 | WF|
This course will introduce students to tools and techniques from the discipline of data science that support efficient and reproducible scientific computing. Students will gain hands-on experience developing complete data analysis projects based on real-world datasets. Lessons will cover the primary tasks that comprise most analyses: data management/acquisition, cleaning, reshaping, manipulation, analysis and visualization, as well as strategies for arranging these constituent parts into cohesive workflows that are verifiable, easily repeatable and consistent with best practices for reproducible computational research. This course will focus on the statistical programming language R but no programming background is necessary.
Terms: Fall | Credits 3 | Grading: A-F
Schedule for HGEN 611
August thru December || Wed, Fri 10:30 AM – 11:50 AM
My interests are in the application and development of statistical genetic methodology to quantify the contribution of genetic and environmental sources to complex traits, human disease and development.