Students study problems arising from the physical, biological, and/or social sciences and the algorithms and theory used to solve them computationally. Included among the problems are numerical methods for maximizing a function and solving a differential equation. Prerequisite: MATH 130 and CSCI 150.
By the end of this course, among other things you should be able to
Overview of the course topics. Refresh those rusty Python skills and learn some new features and functionality.
Understand the basics of notebook programming. Use matplotlib, regression and other statistical libraries to analyze data.
Learn to project 3D map data from geographical information systems into a 2D representation. Incorporate API data to visualize patterns across state and county maps.
Learn to project 3D map data from geographical information systems into a 2D representation. Incorporate API data to visualize patterns across state and county maps.
Cluster multi-dimensional data to find patterns with K-means, and reduce the dimensionality of this data with Principal Component Analysis.
Explore dynamical systems through discrete modeling of differential equations, using both Euler's method and Runga-Kutta.
Use randomness to model and integrate solutions for complex problems.
Use randomness to model and integrate solutions for complex problems.
The purpose of this project, worth 25% of your final grade, is to improve your research, writing and communication skills as well as give you an opportunity to explore in-depth a particular domain with your scientific computing skills.
Finding roots, maxima and minima of functions, with Newton's method, simulated annealing, and genetic algorithms.
Individual and grid-based approaches to modeling complex simulations.
Analysis of patterns, thresholds, and filters for processing time-series signals.
Analysis of patterns, thresholds, and filters for processing time-series signals.
It is the policy of Hendrix College to accommodate students with disabilities, pursuant to federal and state law. Students should contact Julie Brown in the Office of Academic Success (505.2954; brownj@hendrix.edu) to begin the accommodation process. Any student seeking accommodation in relation to a recognized disability should inform the instructor at the beginning of the course.
Please refer to the CSCI Academic Integrity Policy.
After assignments are returned, you are welcome to revise and resubmit your work. Each submitted revision will be graded anew, the original and revised grades will be averaged to produce a new grade for that assignment. Revisions may be submitted anytime until the start of the final exam period.
No late work will be accepted. Any work not submitted on time is a zero. However, you may submit a solution after the deadline to qualify under the revision policy. In effect, this means that late work can earn up to half credit.
You may miss three class days with no penalty. These can be for sports travel, school sanctioned activities, sick, etc. Every subsequent absence will result in a 4% penalty on your final grade.