Bachelor of Science in Computer Science Online

This course introduces students to computer programming, using the language Java. It teaches the primary constructs common to many programming languages--variables, branching, looping, methods, and arrays--and also introduces object-oriented program design.

This is a continuation of the study of programming begun in Computer Programming I. Advanced features of the programming language introduced in Computer Programming I are covered. Problems requiring larger programs are introduced with particular emphasis given to the importance of the algorithms used. Topics covered include: string processing, data structures and recursion.

This course is an introduction to techniques used for structuring data to be stored in various devices. Theory of database design and the implementation of such designs is studied. Topics covered include: the definition and normalization of database designs, the SQL data design language (DDL), and the manipulation of databases designed in SQL via servlets written in the Java programming language.

This course offers a formal study of the basic structures used for storing data and an analysis of the algorithms, which act on data structures. The course builds on the material presented in Computer Programming I and II. This material is made more rigorous with an emphasis on the analysis and design of efficient algorithms. Topics covered include review of basic data structures, basic graph theory with algorithms for finding paths and spanning trees, techniques of design and analysis for (internal and external) sorting, merging and searching, algorithms for hashing, garbage collection and compaction.

This course offers an introduction to the formal study of programming language specification and analysis. Several programming languages (both compiled and interpreted) will be studied in terms of their features and limitations. Topics covered include formal language definition (using Backus-Naur Form and Java as an example), a comparison of several languages in terms of data types and structures, control structures and run-time considerations.

This course is an introduction to computer architecture and its relation to programming in C on the UNIX operating system. General concepts and techniques that apply to a broad range of computers will be covered. These include: representation of data and computer arithmetic, the organization and structuring of the major hardware components of computers, and methods of I/O.

This course provides an introduction to fundamental algebraic, logical and combination concepts from mathematics with applications to various areas of computer science. Topics covered include sets, relations, functions and induction, Boolean algebra and introduction to graph theory.

Today's websites are increasingly dynamic generated by scripts and database calls. This course teaches students how to build dynamic websites with Ajax, Linux, Apache, MySQL, and LAMP/WAMP (today's most popular frameworks).

Software development and user experience design are distinct skillsets, but projects to address real-life problems require simultaneous application of each by teams working together. MAC 3060, "Interactive Media-System Design," will meet in conjunction with CAM 4030, "Interactive Media-User Experience Design." Working in teams of students from both departments, students will develop mobile applications or web applications addressing real life design problems. Projects will be brought by actual clients, and students will engage with the clients, and work within formal process frameworks used in industry.

All students majoring in Computer Science are required to complete a year-long Senior Evaluation in their senior year. A Senior Evaluation represents the highest point of a student's degree in Computer Science. A Senior Evaluation is typically a well-defined project whose end result is a specific deliverable software. An application, an empirical study, a survey, or replicating an existing result are example categories of projects. A Senior Evaluation has an expectation of producing new knowledge or advancement in a specific computer science area. Identifying a project is typically done in the fall semester of the senior year and the actual project is developed in the spring semester. Therefore, Senior Evaluation is split into two courses: Senior Evaluation Proposal and Senior Evaluation. In the fall semester, students will explore project possibilities and do background research and by the end will choose a project they will be developing and delivering in the spring semester. Students are required to submit and present the Senior Evaluation proposals (1-page) in the fall semester. In the spring semester, students are required to submit a formal Senior Evaluation Report to their advisors a week before they present the Senior Evaluation.

All students majoring in Computer Science are required to complete a year-long Senior Evaluation in their senior year. A Senior Evaluation represents the highest point of a student's degree in Computer Science. A Senior Evaluation is typically a well-defined project whose end result is a specific deliverable software. An application, an empirical study, a survey, or replicating an existing result are example categories of projects. A Senior Evaluation has an expectation of producing new knowledge or advancement in a specific computer science area. Identifying a project is typically done in the fall semester of the senior year and the actual project is developed in the spring semester. Therefore, Senior Evaluation is split into two courses: Senior Evaluation Proposal and Senior Evaluation. In the fall semester, students will explore project possibilities and do background research and by the end will choose a project they will be developing and delivering in the spring semester. Students are required to submit and present the Senior Evaluation proposals (1-page) in the fall semester. In the spring semester, students are required to submit a formal Senior Evaluation Report to their advisors a week before they present the Senior Evaluation.

Topics in this course will include functions, limits, and continuity; derivatives of polynomials, products, quotients, trigonometric, and implicit functions; applications to related rates, maximum-minimum problems and graphing; anti-derivatives, the Fundamental Theorem of Calculus, and area problems. A computer symbolic algebra component is included.

This course provides an introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: overview of network architectures, applications (HTTP, FTP), network programming interfaces (e.g., sockets), transport (TCP, UDP), flow control, congestion control, IP, routing, multicast, data link protocols, error-detection/correction, multiple access, LAN, Ethernet, wireless networks, and network security.

This course introduces students to the foundations and applications of Artificial Intelligence. AI, also known as Intelligent Systems, is concerned with the design and analysis of software-based autonomous agents, as found in physical systems such as robots and autonomous spacecraft, and increasingly in computer games and simulation systems. Intelligent systems are able to perceive their environment, to act rationally towards their assigned tasks, and to interact with other agents and with human beings. The course covers a body of work underlying these capabilities, including knowledge representations and reasoning mechanisms, problem solving and search algorithms, and machine learning techniques. Computer games are used as an application area motivating much of this work. Prerequisite MAC 2010.

This course introduces students to the core computational technologies involved in the analysis of large data sets, known popularly as "Data Science" or "Big Data." We focus on the data-handling and computational aspects of data handling-sometimes referred to as "Data Engineering"-and touch on statistics from the standpoint of ensuring data cleanliness and testing the computations. We begin with case studies in Big Data analysis, involving social networks, sensor networks, and application logs. We then introduce various tools used in the data pipeline, including Map-Reduce, No-SQL databases, and custom code for data manipulation. Finally we introduce the use of R for obtaining descriptive statistics that can indicate the need for data cleaning or errors introduced in the data pipeline.

This course will provide a basic introduction to of all aspects of cyber-security including business, policy and procedures, communications security, network security, security management, legal issues, political issues, and technical issues. This course provides students basic knowledge and skills in the fundamental theories and practices of Cyber Security.