Computer Science

This course is a continuation of the topics covered in CIS 150 Computer Science I with an introduction to data structures and sorting algorithms. Programming topics covered include inheritance, polymorphism, exceptions, recursion, GUI programming and file and database input/output. Using object-oriented programming (OOP) techniques, this course introduces students to data structures like stacks and queues.

This course teaches data modeling and Structured Query Language (SQL) skills with hands-on implementation. Students will be able to define a well-structured relational database and use database design concepts to create Entity Relationship Diagrams (ERDs) and data dictionaries. Students will apply normalization models and business rules, write and run scripts and create select queries using inner and outer joins, “where” and “order by” clauses, “having” and “group by” clauses and aggregate functions. Students will also create action queries to update, delete and append data and work with SQL to create a two-layer application.

This course introduces students to the fundamentals of systems programming through the Linux application programming interface (API) and the C language. Students will be able to use system calls and C library concepts to develop scripts and applications that interface with the operating system.

This course introduces students to data structures and algorithmic analysis necessary for the design of efficient computer programs. Data structures covered included stacks, queues, linked lists, graphs, trees, heaps and hash tables. This course will also teach a mathematical framework for evaluating algorithm efficiency. Students will be able to analyze algorithms for searching, manipulating priority queues, traversing trees, hashing, sorting and finding the shortest paths in graphs.

This course familiarizes students with basic concepts of elementary statistics. Topics covered include central tendency and variability measures, regression and correlation, probability, confidence intervals, discrete and continuous random variables, the Central Limit Theorem and hypothesis testing.

This course introduces students to discrete mathematics with a primary focus on applications in Computer Science. Topics covered include logic, methods of proof, elementary number theory, set theory, mathematical induction, combinatorics, functions, relations, recursion and the efficiency of algorithms, trees and graphs.

This course introduces the concepts, methods and applications of differentiation. Students will be able to apply concepts like differentiation of polynomial, trigonometric, rational and composite functions. Other topics covered include related rates, a study of limits, optimization problems, curve sketching, antiderivatives and indefinite integration.

This course is a continuation of the topics covered in MAT 211 Calculus I, emphasizing the methods and applications of integration. Students will be able to apply concepts like integration of algebraic, trigonometric, inverse trigonometric, exponential and logarithmic functions. Other topics covered include volumes, areas between two curves, arc length, Sequences and Series, work, fluid pressure and Hospital’s Rule.

This course teaches linear equations and their representations through matrices and in vector spaces. Topics covered include linear and vector equations, Gaussian Eliminations, linear independence, linear transformations, matrix algebra, the inverse of a matrix, vector spaces and bases, subspaces, dimension, rank, determinants, diagonalization, eigenvalues and eigenvectors, inner product, orthogonality and The Characteristic Equation.