Computation (COMP)

This course is designed to introduce students to the process of coding. It assumes no background in programming or computer science and is intended for students of all majors who want to learn more about computation. Students will learn the basic syntax of the python programming language and apply that syntax to basic coding problems involving text and data manipulation. Students will learn to solve their own coding problems by consulting online resources and will take the first steps towards learning how to define a computational problem.

This course is designed to introduce students to scientific computing in python. It assumes some prior experience with the python language and is intended for students of all majors who want to learn more about scientific computing. Students will learn to use common python libraries for working with data. Students will solve instructor-provided scientific problems by first defining those problems computationally and then applying tools from the aforementioned libraries to solve the problems and visualize the results.

This course is designed to facilitate continued development of student scientific computing skills in the field of data visualization and analysis. It assumes some prior experience with the python language and its scientific computing libraries. The course will provide an introduction to parametric statistical techniques including the calculation of variance and variance ratios, the implementation and interpretation of correlation and regression analysis, the student t-test, and Chi-square analysis. Students analyze instructor-provided data sets by summarizing data using computational techniques and applying visualization tools in order to communicate the results.