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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
CHEM 4310 (Overall) | |||||
CHEM 4310 Cormac Toher | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
CHEM 4310 (Overall) | |||||
CHEM 4310 Cormac Toher | |||||
Introduction to Programming for Chemistry
CHEM 4310
School of Natural Sciences and Mathematics
This course will introduce chemistry students to basic computer programming concepts, with an emphasis on topics important for chemistry research such as the retrieval, processing, and analysis of chemistry data. The course will primarily use the Python language, due to its availability and current popularity in scientific programming, and a brief overview of other languages will also be included. Students will learn how to programmatically access online chemistry databases such as the Protein Data Bank and retrieve data, and use the numpy, scipy, and sci-kit learn libraries to analyze chemical data sets and train machine-learning models. 3 credit hours.
Prerequisite: CHEM 3321 or CHEM 3322.
Offering Frequency: Based on student interest and instructor availability
This professor/course combination hasn't been taught in the semesters you selected. To see more grade data, try changing your filters.
Grades: 0
Median GPA: None
Mean GPA: None
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Introduction to Programming for Chemistry
CHEM 4310
School of Natural Sciences and Mathematics
This course will introduce chemistry students to basic computer programming concepts, with an emphasis on topics important for chemistry research such as the retrieval, processing, and analysis of chemistry data. The course will primarily use the Python language, due to its availability and current popularity in scientific programming, and a brief overview of other languages will also be included. Students will learn how to programmatically access online chemistry databases such as the Protein Data Bank and retrieve data, and use the numpy, scipy, and sci-kit learn libraries to analyze chemical data sets and train machine-learning models. 3 credit hours.
Prerequisite: CHEM 3321 or CHEM 3322.
Offering Frequency: Based on student interest and instructor availability
This professor/course combination hasn't been taught in the semesters you selected. To see more grade data, try changing your filters.
Grades: 0
Median GPA: None
Mean GPA: None
Click a checkbox to add something to compare.