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Course Criteria
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4.00 Credits
A first course in programming using a visual, event-driven programming language. Coverage includes algorithmic problem solving, fundamentals of programming, procedures, decisions, repetition, and arrays. Prerequisite: DS 090, MA 112 or higher, or math placement score of 65 or higher.
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4.00 Credits
Introduction to the design of algorithms and their implementation in a high-level programming language. Topics include: algorithm design strategies, programming concepts, programming environment, data structures, searching and sorting methods, and internal representation of data types. Prerequisites: MA 112 and CIS 115 or Math Placement Score of 75 or higher.
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4.00 Credits
Continuation of CIS 120. Topics include: design concepts, abstract data types, use of object libraries, dynamic storage allocation, stacks, queues, link lists, random access files, testing and software engineering practices.
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3.00 Credits
This course is designed to provide a broad-based introduction to the use of computers to enhance personal productivity. Topics to be covered are use of a graphical user interface, word processing, spreadsheet analysis, basic image management related to documents and reports and the fundamentals of Internet publishing.
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0.00 Credits
No course description available.
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1.00 - 3.00 Credits
Selected topics in computer and information sciences. Requires permission of Specialization Coordinator.
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3.00 Credits
Introduction and fundametals of C++ programming, input-output operations, variables, datatypes, arithmetic expressions, control statements, looping, functions, arrays, pointers, strings, structures, and abstract data types.
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1.00 Credits
Advanced concepts in C++ programming, constructors, destructors, classes and operation overloading.
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3.00 Credits
Floating point numbers, representation, and errors; software tools for scientific computing; elementary problems in scientific computing.
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3.00 Credits
Extension of elementary data structures as covered in CIS 121, techniques to organize and access collections of data. Definition, implementation, and use of Classes and Abstract Data Types (ADT). The use of ADTs and objects for solving CIS problems. Network, hierarchical, and relational data models leading to Database Management Systems. Topics include: recursion, search trees, algorithmic complexity, advanced searching and sorting algorithms, and graphs.
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