Data Science for Engineers

Author

Heidi Moulton, Utah State University

Date of Award

5-2025

Degree Type

Thesis

Degree Name

Departmental Honors

Department

Mathematics and Statistics

Abstract

Undergraduate research is a core pillar of Utah State University’s College of Engineering. Many students become involved with research during their Junior and Senior years and begin to generate various forms of data. Most students, however, have received little formal education on how to process data, and there are currently no readily available resources within the College of Engineering. As a Mechanical Engineering and Data Science double major, I found the data processing techniques I learned in my Data Science courses invaluable as an undergraduate researcher, and now as a Mechanical Engineer at Apogee Instruments, I frequently draw upon these skills as I gather and analyze data regarding the products I develop. The Data Science for Engineers project focuses on creating easily accessible data processing training for undergraduate engineering students at USU. It assumes a basic knowledge of the Python programming language (taught to most engineering students through CS 1400 in their sophomore year) and builds from there. It consists of four modules covering a range of topics from basic data manipulation to nonlinear modeling. Each module contains a Jupyter Notebook with code examples and written explanations and is accompanied by related datasets and a series of supplementary YouTube videos. There are 23 videos in total which can be found in the Introduction to Data Science playlist @DataScienceforEngineers.

Recommended Citation

Moulton, Heidi, "Data Science for Engineers" (2025). Undergraduate Honors Capstone Projects. 1028.
https://digitalcommons.usu.edu/honors/1028