BIOL.4072 Data Science for Biologists
Id: 041946 Credits: 3-3Description
The ability to analyze, visualize, and make inferences from large amounts of biological data will become increasingly valuable for future biologists. Data science can be defined as the intersection between computer science, applied statistics, and knowledge of the application domain--in this case, biology. In this class we will apply methods such as generalized linear models, multi-level models, unsupervised learning, and basic neural networks to biological problems. Hands-on activities using programming will give students experience with steps of a data science project, including simulating, exploring, visualizing, drawing conclusions with statistics, and creating a reproducible analysis. No coding or math experience is needed to succeed in this course.
Prerequisites
BIOL.2200, or BIOL.2520, or COMPO.2010, or MATH.2340, or MATH.3220, and Co-req: BIOL.4072L, or Permission of Instructor.
Course prerequisites/corequisites are determined by the faculty and approved by the curriculum committees. Students are required to fulfill these requirements prior to enrollment. For courses offered through online or GPS delivery, students are responsible for confirming with the instructor or department that all enrollment requirements have been satisfied before registering.