By the end of the course, students should be able to:
- Model biological experimental data using probabilistic distirbutions
- Have a working knowledge of the R and Python environments
- Be able to design statistically sound high-throughput experiments
- Cluster, visualize, and summarize large amounts of, and highly multidimensional, biodata
- Devise accurate regression models for variables of interest, given this type of biodata