This course is on modern software engineering. It covers the complete software development process such as requirement specifications, design, coding, testing and maintenance. Various software engineering methodologies for development of large scale quality software will be presented in this course.
IT Project Management is the discipline that applies management principles to the development of information system projects. It uses techniques developed by Industrial Engineers and used by other engineers and business managers to bring in projects within time and budget. This course supplements Software Engineering by focusing on the management aspects of investing in the development of information systems.
This course provides necessary tools to develop mathmetical maturiy through the study of important topics such as comvinatorial analysis, discrete structures, algorithmic thinking and mathemetical reasoning. Topics include Advanced Enumeration Methods, Recurrence Relations (Equations), Graph Theory, Automata and Formal Languages, Proof Techniques and Probality and Statistics.
This course provides various methodologies to design and analyze algorithms. Topics include incremental, divide-and-conquer, dynamic programming, greedy, backtracking, and branch-and-bound methodologies. Additional topics include sorting and searching algorithms, and computational complexity and Intractability.
This course covers various concepts associated with design and construction of data base systems. Topics include data base architecture, relational model, relational languages (SQL), normalization theory, Entity-Relationship theory and physical data base design. Students will develop a simple data base system.
This course serves as an introduction to different techniques and tools for the design of web applications. Topics covered include web applications flow, object oriented programming, design of classes, dynamic content, scripting languages, implicit objects, and database accessing. Students will be expected to understand and apply these concepts into the generation of sample websites.
Information is the discipline that applies the methodologies of science and engineering to information. It concerns organizing data into information, learning knowledge from information, learning new information from knowledge and making decisions based on the knowledge and information learned. This course concerns computational methods for analyzing data and processing information in applications to business decisions.
This course provides an in-depth study of the principles of object oriented programming, including Classes, Objects, Methods, Arrays, Inheritance, and Polymorphism. Within this framework, the course will cover Sorting and Searching Arrays, Two-Dimensional Arrays, Exception Handling, and File Input/Output. Emphasis is given to the design of algorithms and program development, involving both numeric computations and string manipulation techniques. A common comprehensive final exam will be given for all sections of CS-207, Programming II—the date of this final exam will be published within the section record each term.
A first course in computer programming from basic through intermediate levels. Content includes designing, implementing and debugging maintainable Java programs, and demonstrating problem solving and algorithm development for applications from business and computer science. Abstract data types and object-oriented methods enhance study of elementary data structures.
This course provides experience implementing and manipulating basic data structures, as well as analyzing their applications in Computer Science. Topics covered will include: Stacks, Queues, Linked Lists, Binary Tree Structures, Heaps, Graphs, and Sorting Algorithms.
Graphics Hardware. Scaling and data charting. Representation of two dimensional objects , Translation and rotation of objects. Two dimensional line clipping. 3-D object representation. Perspective in 3-D object representation. Line clipping and hidden line face removal in 3-D. Efficiency consideration in hidden line and face removal. Lighting and shading. Reflections and shadows, transparent and translucent surfaces. Interactive graphics and associated hardware and software. Software for event handling and device sampling. The light pen with locator pick problems and echoing.
This course serves as an introduction to aspects of Artificial Intelligence applied to the robotics field. Students will learn different techniques to approach problems using simple robotics. Students will be expected to understand the main concepts, research for available resources, and participate in projects where these concepts will be applied.