This course teaches key scientific programming skills and demonstrates the application of these techniques to environmental data analysis and problem solving. Topics include structured programming and algorithm development, flow control, simple and advanced data input-output and representation, functions and objects, documentation, testing and debugging. The course is taught using a combination of the R and Python programming languages.

No Prerequisites

4

Units

Pass no pass

Grading

1, 2, 3

Passtime

Graduate students only

Level Limit

Environmental science

College
These majors only eds
OLIVER R Y
No info found
Summer 2024 . Oliver R Y
NCEAS0100
M T W R F
09:00 AM - 17:00 PM
See All
EDS 221 Horst A M Summer 2023 Total: 0
EDS 221 Horst A M Summer 2022 Total: 0
EDS 212
0 / 30 Enrolled
Essential Math for Environmental Data Science
Oliver R Y
M T W R F
09:00 AM - 17:00 PM
EDS 214
0 / 30 Enrolled
Analytical Workflows and Scientific Reproducibility
Czapanskiy M
M T W R F
09:00 AM - 17:00 PM
100.0% A
EDS 217
0 / 30 Enrolled
Python for Environmental Data Science
Caylor K K
M T W R F
09:00 AM - 17:00 PM