Foundations of Applied Mathematics is a series of four textbooks developed for Brigham Young University’s Applied and Computational Mathematics degree program for beginning graduate and advanced undergraduate students. These are as follows:
- Volume 1: Mathematical Analysis.
- Volume 2: Algorithms, Approximation, and Optimization.
- Volume 3: Modeling with Uncertainty and Data.
- Volume 4: Modeling with Dynamics and Control.
The textbooks are being published by the Society for Indistrial
and Applied Mathematics.
Volume 1 is available now. Volume 2 should be available near June 2018, and the remaining volumes will be available soon thereafter.
This site contains a collection of Python labs that go in tandem with the textbooks. These expose students to applications and numerical computation and reinforce the theoretical ideas taught in the text. The text and labs combine to make students technically proficient and to answer the age-old question, “When am I going to use this?”
Currently available are the Python Essentials labs, which introduce Python and its scientific computing tools, and the Volume 1 labs. Labs for the other volumes are forthcoming.
Students: Getting Lab Materials
Get started by downloading the Python Essentials lab manual. Some of the labs require the use of certain data sets , and every lab has a specifications file for submitting your answers. To access these materials, download git and the Python Essentials specifications files. Unzip the specifications archive, then in a command prompt (Terminal on Linux and Mac or GitBash on Windows), run the following commands to download the data files.
# Navigate to the unzipped specifications folder. $ cd /path/to/your/folder # Run a script to download the data files and move them to the right places. $ bash download_data.sh
Instructors: Teaching from the Labs
At BYU we normally have students do the first six labs from Python Essentials before beginning the regular labs for Volume 1 and Volume 2, and the remaining essentials labs are worked into the curriculum during the rest of the year. But students who have completed the first four essentials labs can probably get started on the regular labs, especially if they find a way to do the next two Essentials labs fairly soon thereafter.
Each lab has a specifications file—a Python file or a Jupyter Notebook with predefined functions for students to implement. Using these spec files allows instructors and teaching assistants to quickly test and grade student submissions.
Additional instructor materials, including solutions files and automated test drivers, are available for instructors and teaching assistants. Please contact us at email@example.com if you would like access to these resources.
Jeffrey Humpherys and Tyler J. Jarvis
Department of Mathematics
Brigham Young University
- E. Evans, Brigham Young University
- R. Evans, University of Chicago
- J. Grout, Drake University
- J. Whitehead, Brigham Young University
S. McQuarrie, M. Cook, A. Henriksen, R. Murray, A. Zaitzeff
J. Adams, J. Bejarano, Z. Boyd, M. Brown, A. Carr, T. Christensen, M. Cook, R. Dorff, B. Ehlert, M. Fabiano, A. Frandsen, K. Finlinson, J. Fisher, R. Fuhriman, S. Giddens, C. Gigena, M. Graham, F. Glines, M. Goodwin, R. Grout, J. Hendricks, A. Henriksen, I. Henriksen, C. Hettinger, S. Horst, K. Jacobson, J. Leete, J. Lytle, R. McMurray, S. McQuarrie, D. Miller, J. Morrise, M. Morrise, A. Morrow, R. Murray, J. Nelson, E. Parkinson, M. Probst, M. Proudfoot, D. Reber, C. Robertson, M. Russell, R. Sandberg, J. Stewart, S. Suggs, A. Tate, T. Thompson, M. Victors, J. Webb, R. Webb, J. West, and A. Zaitzeff.
This work is licensed under the Creative Commons Attribution 3.0 United States License. To view a copy of this license please visit http://creativecommons.org/licenses/by/3.0/us/.
This project is funded in part by the National Science Foundation, grant no. TUES Phase II DUE-1323785.