2018 Spring
ESPM 288 001 - LAB 001
Reproducible and Collaborative Data Science
Carl Boettiger, Dana Paige Seidel
Class #:39303
Units: 3
Offered through
Environmental Science, Policy, and Management
Current Enrollment
Total Open Seats:
0
Enrolled:
Waitlisted:
Capacity:
Waitlist Max:
No Reserved Seats
Hours & Workload
4 hours of instructional experiences requiring special laboratory equipment and facilities per week, and 7 hours of outside work hours per week.
Other classes by Carl Boettiger
Other classes by Carl Boettiger
Course Catalog Description
Introduction to principles and tools for reproducible and collaborative data science, including data curation and cleaning, version control, virtual machines, scripted work flow, hypothesis-driven exploratory data analysis, data visualization, and communication. Students will be introduced to git, Python,R, and LaTeX. The class will navigate a series of problem-driven analyses, focused on case studies and independent projects, leading to reproducible products that allow updated analyses as new data become available. Projects by first year trainees will be presented at the Annual Symposium.
Rules & Requirements
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
Textbook information is not available for Spring 2018.
Associated Sections
None