CSC - Computer Science

Course introduces mathematical induction and recursion; set theory; relations and functions; logic, combinatorics, graph theory and trees; Boolean Algebra, probability, matrices and analysis of algorithms. Credit toward graduation cannot be received for both MAT 144 and CSC 144.

A first course in computer programming from basic through intermediate levels. Content includes designing, implementing and debugging maintainable C++ 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.

A first course in computer programming from basic through intermediate levels. Introduces a disciplined approach to problem-solving and algorithm development using the Java programming language for applications from business and computer science. Abstract data types and object-oriented methods enhance study of elementary data structures. Covers: selection, repetition, and sequence control structures; program design, testing, and documentation using good programming style; block-structured high-level programming language; and arrays, records, and files.

A first course in computer programming from basic through intermediate levels. Content includes designing, implementing and debugging maintainable Python 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.

An introduction to the tools available for solving numerically intensive applications that occur in scientific and engineering fields. The study of numerical algorithms will be supported by the use of a computer algebra system. Network utilities will enable students to use the Internet for communication and learning purposes.

Course introduces C++ programming language. Content focus is on solving numerically intensive applications present in scientific and engineering fields. Numerical algorithms implemented using object-oriented programming tools and elementary data structures.

Course introduces Java programming language. Content focus is on solving numerically intensive applications present in scientific and engineering fields. Numerical algorithms implemented using object-oriented programming tools and elementary data structures.

Course introduces Python programming language. Content focus is on solving numerically intensive applications present in scientific and engineering fields. Numerical algorithms implemented using intermediate programming tools and elementary data structures.

Introduction to concepts involving the fundamentals of artificial intelligence for solving real world applications. Machine Learning (ML) problems will be emphasized including data science for analyzing and manipulating data, supervised and unsupervised learning, deployment of machine learning models as web services, and neural networks. Course includes use of the Python programming language and its fundamental ML libraries.

A survey of the various levels of hierarchical computer architectures and design. The analysis of internal and external memory models, busses, I/O devices, and CISC/RISC processor strategies are covered. Additional topics include the instruction formats and addressing schemes of architectures such as Intel, MIPS, ARM, and the JVM; parallel and vectorized multiprocessors and multicomputer systems; pipelining; parallel programming; secure and optimized programming techniques; coding and compression schemes; assembly programming in MIPS and MARIE.

An introductory course of computer security principles and practices with applications to databases and software systems. An emphasis is placed on securing database authentication and authorization processes; and, securing systems through responsible software development and scripting techniques. Credit toward graduation cannot be received for both CIS 206 and CSC 206.

Course serves as an overview of the foundations of data science. Specific topics include a synopsis of data management, data collection, information extraction and reporting, basic data visualization and presentation procedures, exploratory and predictive data analysis. Emphasis will be placed on real-world problem-solving techniques using various mathematical and scientific concepts. This course includes the use of various technological tools and the Python programming language with its standard libraries and supplemental predeveloped libraries.

A second course in computer programming using the C++ programming language that provides a survey of data structures including files, lists, sets, trees, tables, queues, stacks, graphs, and other classes. Content covers: utilization of object-oriented design techniques to implement solutions for large-scale problems; program verification and complexity analysis; dynamic concepts; sorting and searching algorithms; abstract data types; recursion.

A second course in computer programming using the Java programming language that provides a survey of data structures including files, lists, sets, trees, tables, queues, stacks, graphs, and other classes. Content covers: utilization of object-oriented design techniques to implement solutions for large-scale problems; program verification and complexity analysis; dynamic concepts; sorting and searching algorithms; abstract data types; recursion.

A second course in computer programming using the Python programming language that provides a survey of data structures including files, lists, sets, trees, tables, queues, stacks, graphs, and other classes. Content covers: utilization of object-oriented design techniques to implement large-scale problems; program verification and complexity analysis; dynamic concepts; sorting and searching algorithms; abstract data types; recursion.

An intermediate programming course that continues the development of object-oriented techniques using data structures with an emphasis on graphs, sets, maps/tables, heaps, and trees; foundational analysis and design of various algorithms that exhibit recursion, backtracking, divide and conquer, greedy strategies and dynamic programming techniques; random number generation; cryptography; introductory parallel programming techniques; includes an analysis of time and memory complexity using discrete metrics; sorting and searching techniques. The course is offered with an option for choice of programming languages (C++ or Java or Python).

Course covers a variety of different topics during different semesters. Topics will be selected from among current advances in hardware and software technology. Typical course concentrations might be Introduction to Parallel Programming or Artificial Intelligence. Check with Instructor and latest college class listings for details. Course may be repeated up to three times. Fee Varies. Prerequisite may vary by topic.