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| Name | Grades | Rating | |||
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GEOS 5332 (Overall) | |||||
GEOS 5332 Steven Pirouz | |||||
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| Name | Grades | Rating | |||
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GEOS 5332 (Overall) | |||||
GEOS 5332 Steven Pirouz | |||||
Machine Learning for Earth and Environmental Sciences
GEOS 5332
School of Natural Sciences and Mathematics
This course delves into predictive modeling to extract valuable insights from geological data, climate patterns, and natural resource management. Students will apply cutting-edge machine learning techniques to address environmental challenges, predict natural disasters, and develop sustainable solutions. 3 credit hours.
Offering Frequency: Each year
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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Machine Learning for Earth and Environmental Sciences
GEOS 5332
School of Natural Sciences and Mathematics
This course delves into predictive modeling to extract valuable insights from geological data, climate patterns, and natural resource management. Students will apply cutting-edge machine learning techniques to address environmental challenges, predict natural disasters, and develop sustainable solutions. 3 credit hours.
Offering Frequency: Each year
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.