Rachel Lyn-Salmon Frisbie - Overview

Back to Overview for Rachel Lyn-Salmon Frisbie

CMSE 201 - Computational Modeling and Data Analysis I

Computational modeling using a wide variety of applications examples. Algorithmic thinking, dataset manipulation, model building, data visualization, and numerical methods all implemented as programs.

Average Grade - 3.458
Median Grade - 4.0
2486 total students

Latest grades from Spring 2026

See detailed grade info for this course

Back to Overview for Rachel Lyn-Salmon Frisbie

CMSE 202 - Computational Modeling and Data Analysis II

Standard methods and tools for computational modeling and data analysis using simulation techniques, data mining, and machine learning.

Average Grade - 3.795
Median Grade - 4.0
194 total students

Latest grades from Spring 2023

See detailed grade info for this course

Back to Overview for Rachel Lyn-Salmon Frisbie

CMSE 402 - Data Visualization Principles and Techniques

Core principles, methods, and techniques of effective data visualization. Visualization toolkits. Vector and scalar data. Multivariate visualization. Relationship between data analysis and visualization.

Average Grade - 3.536
Median Grade - 4.0
291 total students

Latest grades from Spring 2026

See detailed grade info for this course

Back to Overview for Rachel Lyn-Salmon Frisbie

CMSE 890 - Selected Topics in Computational Mathematics, Science, and Engineering

Topics selected to supplement and enrich existing courses.

Average Grade - 3.917
Median Grade - 4.0
163 total students

Latest grades from Spring 2025

See detailed grade info for this course

Back to Overview for Rachel Lyn-Salmon Frisbie

CMSE 928 - Applied Machine Learning

Average Grade - 3.955
Median Grade - 4.0
11 total students

Latest grades from Spring 2026

See detailed grade info for this course