Overview
Description
This course will cover the basics of Python programming and the common Python libraries used in scientific research. While examples will draw primarily from the Earth Sciences, the skills learned are readily applicable to other disciplines; students from other programs are most welcome to take this course. The course is divided into four sections: Python Fundamentals, Scientific Python, Data Visualizations, and Introduction to Machine Learning.
Requirements
Prerequisites
- higher
MATH 127
Original catalog text
Prerequisites
Prerequisite(s): MATH 127 (Precalculus II) or higher
Units
Lecture3
Catalog Details
Offering
Offered: Every Spring
Terms
spring
Attributes
Standard
Learning Outcomes
- articulate an understanding of essential computer programming fundamentals and paradigms.
- load, analyze, and display scientific datasets using Python.
- apply common scientific Python modules and become comfortable approaching new modules that are not covered explicitly in the course.
- utilize data visualization techniques and practice making publication-quality scientific figures.
- develop problem solving skills through the lens of Python.