Computer Science Concentration

Students learn the history and basics of computing, as well as the fundamentals of programming. General topics include: the history of computing, number systems and classical computing, Boolean logic, algorithm design and implementation, and modern computer organization. Programming topics include: memory and variables, mathematical operations, basic input and output, decision making, repetitions, functions, and arrays.

Students will learn the history and basics of computing as well as the fundamentals of Python programming. General topics include: the history of computing, number systems, Boolean logic, algorithm design and implementation, and modern computer organization. Programming topics include: memory and variables, data types, mathematical operations, basic file I/O, decision-making, repetitions, functions, and list basics.

This course builds on the content from Introduction to Programming. Students study the Object Oriented Programming (OOP) Paradigm with topics such as objects, classes, encapsulation, abstraction, modularity, inheritance, and polymorphism. Students examine and use structures such as arrays, structs, classes, and linked lists to model complex information. Pointers and dynamic memory allocation are covered, as well as principles such as overloading and overriding. Students work to solve problems by selecting implementation options from competing alternatives.

This course continues the material from Python Programming beginning with lists and basic structures. Then, the focus moves toward Object-Oriented Programming (OOP) that includes topics such as objects, classes, encapsulation, abstraction modularity, memory management, inheritance, and polymorphism. Advanced Python language features like iterators, generators, lambdas, and comprehensions are also covered.

Students compare and contrast a variety of data structures with Python. Students compare algorithms for tasks such as searching and sorting, while articulating efficiency in terms of time complexity. Students implement data structures and algorithms to support solution designs.

Students compare and contrast a variety of data structures. Students compare algorithms for tasks such as searching and sorting, while articulating efficiency in terms of time complexity. Students implement data structures and algorithms to support solution designs.

This course will introduce students to database design, Structured Query Language (SQL), normalization, and relational database theory. Traditional relational databases will be contrasted with NoSQL paradigm databases including document-oriented, key-value store, and graph. Students will gain hands-on experience writing database applications.

Students work with topics in algebra, trigonometry, functions, and curve-sketching in the Cartesian plane as preparation to take a course in Calculus. After a brief algebra review, precalculus topics include polynomial, rational, inverse, exponential, and logarithmic functions, and an introduction to trigonometry and trigonometric functions.

This course teaches the common application of calculus theories. You will investigate basic topics of differential and integral calculus with a specific emphasis on applications. You will perform differentiation and integration of algebraic and transcendental functions, apply optimization techniques, and learn to formulate and solve differential equations.

Students will learn the concepts, techniques, and structures of discrete mathematics necessary for the software engineer, including logic, sets, functions, relations, Boolean algebra, and combinatorics. The course also introduces the concept of mathematical proof.