Gardner, William Payton

English

University of Montana

University of Montana ScholarWorks at University of Montana University of Montana Course Syllabi, 2021-2025 Spring 2-1-2022 GEO 391.01: Computational Methods in the Earth and Environmental Sciences William Payton Gardner University of Montana, Missoula Follow this and additional works at: https://scholarworks.umt.edu/syllabi2021-2025 Let us know how access to this document benefits you. Recommended Citation Gardner, William Payton, "GEO 391.01: Computational Methods in the Earth and Environmental Sciences" (2022). University of Montana Course Syllabi, 2021-2025. 541. https://scholarworks.umt.edu/syllabi2021-2025/541 This Syllabus is brought to you for free and open access by ScholarWorks at University of Montana. It has been accepted for inclusion in University of Montana Course Syllabi, 2021-2025 by an authorized administrator of ScholarWorks at University of Montana. For more information, please contact scholarworks@mso.umt.edu. GEO391-ST: Computational Methods in the Earth and Environmental Sciences Spring 2021 University of Montana Instructor: Dr. Payton Gardner Email: payton.gardner@umontana.edu Office: CHCB 353 Phone: 406-243-2458 Class meetings: Tuesday-Thursday 2:00pm-3:20pm Dr. Gardner Office hours: T 11-12. TA: Supanut (Boon) Suntikoon (PhD Student) Email: supanut.suntikoon@umontana.edu Office Hourse: M-F: 11:00am-1pm Zoom link: On Moodle Note: This Course has a Moodle Site. Additional reading material, problems sets and other information will be posted there with frequent updates, so check the site often. Description: This course is designed to familiarize students with computers and the use of computers as tools in the Earth and Environmental Sciences. Students will gain a broad overview and practical experience in the fundamentals of writing computer programs and common techniques in the management, exploration and analysis environmental data. Emphasis will be on learning the fundamentals of mid-level languages for data analysis and modeling. The course de-emphasizes the mathematical complexities of the methodologies in favor of generating an intuitive understanding, but we will introduce some linear algebra and statistical concepts. Learning outcomes: In this course, students will: • Know the fundamental components of a computer. • Be able to use essential components of computer coding including: data structures, array manipulation, loops, functions, and libraries. • Be able to use computer scripts to manipulate, analyze and visualize a variety of data types. • Understand geospatial data types and be able to plot geospatial vector and raster data. • Be introduced to panoramic and practical understanding of computational methods commonly used in the fields of Earth and Environmental Sciences. • Be able use the Python programming language to apply these methods for environmental data analysis, statistical inference, hypotheses testing, and physically modeling Environmental Systems. Prerequisites: High school physics and algebra. Interest in spending time programming computers Grades: 60% class activities; 40% midterm and final Text books: We will use two text books that are made available online by their authors at no cost. The books will be available on Moodle at the beginning of the semester. Additional reference material will be uploaded to Moodle as necessary. • Python primer: – Severance, C. Python for Everybody - Exploring Data using Python 3. https://www.py4e.com/book.php • Basic statistics: – Diez, D.; Cetinkaya-Rundel, M., Barr, C. OpenIntro Statistics. 4th edition. 2019. https://www.openintro.org/book/os/ Tentative list of topics: Date Topic 01/18/22 What is a computer? 01/20/22 Interacting with computers 01/25/22 Interacting with Python 01/27/22 Debugging 02/01/22 Condiitionals/Loops/Interation 02/03/22 Functions 02/08/22 Data structures 02/10/22 Numpy/Library/Array/Array Function 02/15/22 Data Import/Pandas 02/17/22 Plotting/Matplotlib 02/22/22 Plotting Geospatial/Geopandas 02/24/22 Downscaling/Upscaling 03/01/22 Random Variables, CDF and PDF 03/03/22 Normal Distribution/Sampling/Modeling 03/08/22 Recurrence Intervals 03/10/22 Standard Error/Confidence intervals 03/15/22 Hypothesis Testing 03/17/22 MID TERM 03/22/22 SPRING BREAK 03/24/22 SPRING BREAK 03/29/22 Linear systems introduction 03/31/22 Solution of linear systems 04/05/22 Least Sqares/Regression 04/07/22 Propagation of uncertainty in linear systems 04/12/22 01/14/22 Simulation of physical systems 04/19/22 differential equation solutions 04/21/22 Uncertainty/Paramterization/Monte Carlo 04/26/22 Incorroporating Data - optimization 04/29/22 05/03/22 Non-linear uncertainty (MCMC) 05/05/22 05/11/22 Final Exam - 3:20-5:20 POLICIES Emailing We may occasionally conduct email correspondence with class members and we will use official UM email addresses. All email sent to us must originate from your official UM email address (email originating from non-UM addresses will not be read or responded to). Sorry, but this is the law we are required to follow. Attendance No formal attendance will be taken. However, the format of this course requires class attendance for success. Substantial course content (i.e., graded in-class exercises and discussions) and information transfer will only occur in class. Due dates All assignments are due at the start of class on designated due date. Disabilities The University of Montana assures equal access to instruction through collaboration between students with disabilities, instructors, and Disability Services for Students. If you think you may have a disability adversely affecting your academic performance, and you have not already registered with Disability Services, please contact Disability Services in Lommasson Center 154 or 406.243.2243. I will work with you and Disability Services to provide an appropriate modification. Conduct Code All students must practice academic honesty. Academic misconduct is subject to an academic penalty by the course instructor and/or a disciplinary sanction by the University. All students need to be familiar with the Student Conduct Code. The Code is available for review online at: http://www.umt.edu/vpsa/policies/student conduct.php 

GEO 391.01: Computational Methods in the Earth and Environmental Sciences

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GEO 391.01: Computational Methods in the Earth and Environmental Sciences

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