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Students will learn concepts and trends in computer science. Students will gain an understanding of the terminology, current issues and changes in the technology of computing. Students will learn to use major application packages, such as word processing, spreadsheet and relational database. Students will develop structured programs using a high-level language. Students will also examine social and ethical issues in computing.
Students will learn fundamental programming concepts using the C++ programming language. Principles of problem solving and algorithm design will be introduced as well as basic techniques for data representation and manipulation. Students will learn how to design, develop, test and document well-structured programs. Students may earn credit for only one of INFO 1112 and CPSC 1103, as they are equivalent courses.
Prerequisite(s): Level B1 as defined in the Math Alternatives Table
Students will learn fundamental programming design and implementation concepts in the context of object-oriented programming. Students will review elementary concepts and learn more advanced concepts such as: data structures, objects, object interaction, inheritance, polymorphism, interface, abstract classes, and exception handling. Students will also be introduced to concepts and design principles of event-driven programming and graphical user interfaces. Students will learn methods for good analysis, design and style. Students may earn credit for only one of INFO 2313 and CPSC 1204, as they are equivalent courses.
Students will learn fundamental tools of data and program organization including object-oriented programming, algorithms, data abstraction and data structures.They will learn to implement and to use data structures such Lists, Stacks, Queues, Trees, Hash Tables, and Graphs. Students will learn algorithms for tasks including searching and sorting. They will learn to use mathematical tools for analyzing algorithm efficiency.
Cross-listing: INFO 2315
Students will learn computer simulation and modeling techniques. They will learn simulation methodologies and techniques for random number and stochastic variate generation. They will also learn simulation design, analysis and estimation based on endogenously created data, simulation model validation and variance reduction. Students will implement simulation models for real-life applications using a computer programming language.
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