Computer Science

An introduction to computational problem-solving using Python. Hands-on labs are used to motivate basic programming concepts, including basic data types and structures, functions, conditionals, and loops. Additional topics may include building and scraping HTML webpages. The course is recommended for all who wish to explore data science and/or computer science.

Prerequisite(s): Math ACT score of at least 21 or permission of instructor.

A project-based continuation of the techniques developed in CMPSC 1100 Python Programming I. Topics include object-oriented programming, algorithm design and analysis, data structures, and general problem-solving techniques (such as recursion) while following industry-standard software development principles.

Prerequisite(s): Grade of "C" or better in CMPSC 1100 Python Programming I or permission of instructor.

See PHYS 2600 Computer Architecture and Interfacing.

This course, built in collaboration with Google, will teach you how to understand and use data structures. Data structures are used by almost every program and application to store, access and modify the vast quantities of data that are needed by modern software. By the end of this course you'll learn what data structures are and learn how to use them in the applications you build. This online class has optional live sessions. This course is an online class offered through the Lower Cost Models Consortium. The class has optional live sessions. Prerequisite(s): CMPSC 2100 Python Programming II.

This course explores algorithms from a coding-focused perspective, using Python. Students will learn about the issues that arise in the design of algorithms for solving computational problems and will explore a number of standard algorithm design paradigms and their applicability. Students will also become familiar with concepts of runtime, recursion, implementation and evaluation. This course features a heavy emphasis on practical application of algorithms to common development and engineering challenges. This course is an online class offered through the Lower Cost Models Consortium. The class has optional live sessions.

Prerequisite(s): CMPSC 3000 Data Structures and MATH 1600 Calculus I.

An introduction to calculus of a single variable. Topics include limits, continuity, differentiation, and beginning integration with applications. Assignments are given that help build proficiency in the use of a computer algebra system.
Prerequisite(s): Math ACT score of at least 27, or a grade of "C" or better in MATH 1470 Trigonometry or MATH 1400 Pre-Calculus, or permission of the instructor.
(Normally offered each semester.)