Introduces basic concepts in computer science and computational problem solving through the design of algorithms and computational processes, modularization, and abstraction. Also introduces the processes of programming and software development as a means to put solutions into practice. Has a required lab, but does not satisfy the 'Natural Science with Laboratory' requirement.

A second course in computer science and computational thinking, focusing on data structures and advanced programming. Topics include implementation and applications of data structures such as stacks, queues, linked lists, trees and graphs. Also introduces performance analysis of algorithms. Has a required lab, but does not satisfy the 'Natural Science with Laboratory' requirement.

This course will prepare students for advanced computer science courses. Using a production-level programming language as a tool, students will implement advanced data structures and algorithms. Students will also study advanced programming concepts and strategies for algorithm development and analysis. Through programming projects, students will explore complex tree structures, graph algorithms, greedy algorithms, dynamic programming, divide-and-conquer algorithms, and parallelism/concurrency.

This course covers the basic instruction set, architecture, and organization of a modern computer. Fundamentals of translating higher-level languages into assembly language, and interpretation of machine languages by hardware are studied. A model of computer hardware organization is developed from the gate level upward. Topics include logic circuits, micro-architectures and microprogramming, machine architectures, and software-hardware interface issues.

Trees, graphs and networks; further analysis of algorithms and their efficiency.

An introduction to the theoretical models used to understand the capabilities and fundamental limitations of computational devices. Topics include formal languages, automata, grammars, computability, reductions, and complexity.

Introduction to the basic concepts of calculus and their applications. Functions, derivatives and limits; exponential, logarithmic and trigonometric functions; the definite integral and the Fundamental Theorem of Calculus.

Techniques of integration, applications of integration, separable first-order differential equations, convergence tests for infinite series, Taylor polynomials and Taylor series.

Basic set theory, combinatorics (the theory of counting), finite difference equations, and graph theory with related algorithms.