Southwestern Oklahoma State University Undergraduate Catalog 2024-2025
through use of classic data structures list, stack and queue; and object- oriented thinking and design. Emphasis will be on program design, modularity, debugging, and documentation. Source code management is practiced in paired programming projects. Prerequisite: COMSC 1033 . F, S COMSC 1103 INTRODUCTION TO INFORMATION SECURITY & ETHICS This course is an overview of the fundamentals of a practical information security program with special emphasis on information security awareness, security systems development, implementation, maintenance, and ethics. This course provides an integrated, comprehensive, up-to-date coverage of the information security policies, process, computer science techniques, security tools, and awareness vital to information security. The classroom instruction provides a practical approach (case scenarios) of both the principles and practice of information, computer, and network security for the enterprise and home. F, S COMSC 2011-4 SEMINAR IN COMPUTER SCIENCE Group study of specified beginning and intermediate level topics in This course provides a comprehensive introduction to machine learning, focusing on the development of algorithms that allow computers to learn from and make decisions based on data. The curriculum includes supervised and unsupervised learning, model evaluation, and techniques for improving model performance. Prerequisite: ARNTL 1003. D COMSC 2043 DISCRETE STRUCTURES Introduction to discrete mathematics for computer science. Sets, functions, propositional and predicate logic, Boolean algebra, graph theory, matrices, proof techniques, combinatorics, and finite state machines. Prerequisites: COMSC 1053 and MATH 1513. F, S COMSC 2073 DATA VISUALIZATION computer science. Credit: 1-4 semester hours. D COMSC 2023 MACHINE LEARNING This course provides a comprehensive introduction to the principles and practices of data visualization. Students will learn how to transform complex data into compelling visual narratives that can effectively communicate insights and support decision-making. Prerequisites: Basic knowledge of statistics and ARNTL 1123 (recommended). D COMSC 2413 DATA STRUCTURES This course introduces the techniques needed to manipulate commonly occurring data structures. It begins reviewing the Python approach to data abstraction and continues treatment of how to create and maintain various data structures as arrays, stacks, queues, linked lists, binary search trees, hash and binary heaps. Algorithms (e.g., divide and conquer, time complexity, sorting, Big O) and efficiency are also discussed. Prerequisite: COMSC 1053. F COMSC 2463 PROGRAMMING IN C# WITH UNITY Introduction to programming in C# for students with programming experience. Programming topics include advanced applications using C# such as unity game design. Prerequisite: COMSC 1033. S COMSC 2473 PROGRAMMING IN C++ Emphasis in this course will be object-oriented C++. Topics include definition of class, data abstraction, pointers, member functions, friend functions, static class member, operator overloading, inheritance, virtual function, polymorphism, template, exception handling, reusability, generic algorithms in C++, introduction to Standard Template Library, files and standard input/output, single and multi-dimensional arrays, and advanced algorithms for searching and sorting. Extensive programming exercises in C++ are required. Prerequisite: COMSC 1033 or familiarity with a modern programming language. S COMSC 2603 NETWORK SECURITY This course will take an in-depth look at network defense concepts and techniques. It will examine theoretical concepts that make the world of networking unique. This course will also adopt a practical hands-on approach when examining network defense techniques. Along with examining different network defense strategies, this course will explore the advancement of network implementation, as well as timeless problem- solving strategies. Prerequisite: COMSC 1103. F, S
DEPARTMENT OF COMPUTER SCIENCE Artificial Intelligence ARNTL 1003 INTRODUCTION TO ARTIFICIAL INTELLIGENCE This course is designed for beginners and provides a foundational overview of Artificial Intelligence (AI). The course focuses on AI’s development, its practical applications, and its societal implications. Students will learn about concepts including algorithms, machine learning, and neural networks. D ARNTL 1123 INTRODUCTION TO DATA SCIENCE This course provides an introduction to the field of Data Science, offering students a comprehensive overview of the principles, techniques, and tools used to analyze, visualize, and interpret complex data. Students will learn the foundational concepts of data collection, cleaning, and processing, along with statistical analysis and machine learning algorithms essential for extracting meaningful insights from data. Prerequisites: Basic knowledge of statistics and COMSC 1033. D ARNTL 3033 RECENT TRENDS IN ARTIFICIAL INTELLIGENCE This course explores the latest advancements and emerging trends in the field of artificial intelligence (AI). Students will gain insights into cutting- edge AI technologies, research breakthroughs, and innovative applications across various industries. The course emphasizes practical knowledge, critical analysis, and hands-on experience with the most current AI tools and techniques. Prerequisites: ARNTL 1003 . D ARNTL 3133 AI ETHICS This course provides a comprehensive overview of the ethical, social, and legal implications of artificial intelligence (AI). Students will engage with theoretical frameworks and case studies to critically examine the challenges and responsibilities associated with AI development and deployment. Prerequisites: ARNTL 1003 and COMSC 2023 . D ARNTL 3233 AI / HUMAN INTERACTION This course explores the dynamic interplay between artificial intelligence (AI) and human interaction, focusing on the design, implementation, and impact of AI systems that interact with humans. Students will examine the principles of human-centered AI, user experience (UX) design, ethical considerations, and the societal impacts of AI systems that are integrated into daily life. Through theoretical studies and practical projects, students will learn to create AI systems that enhance human capabilities and improve user experiences. Prerequisites: ARNTL 1003. D Computer Science COMSC 1023 COMPUTERS & INFORMATION ACCESS Introduction to computers, computer software, and the use of computers to access information for general education students. Includes an introduction to computer concepts and security, operating systems, and computer applications, including Word, Excel, PowerPoint, and Access. F, S, SU NOTE: The course curriculum is based on the Windows operating system. Students who do not have access to a Windows computer should plan to use computers in the SWOSU computer labs whether taking this course online or face-to-face. COMSC 1033 COMPUTER SCIENCE I This is an introductory programming course. This course focuses on algorithm design, problem-solving strategies and program design. Topics covered include variables, types, expressions and control structures. Additional topics are standard input/output; file input/output; file streams; single and multi-dimensional arrays; searching; sorting; and recursion and its relation to iteration. This course also introduces object-oriented programming concepts such as classes and objects; syntax of class definitions; methods and parameter passing. Source code management is introduced. F, S COMSC 1053 COMPUTER SCIENCE II This course is a continuation of Computer Science I. Object-oriented programming concepts such as class inheritance, encapsulation and polymorphism are covered. Topics covered include abstract classes; interfaces; GUI programming; event-driven programming; data abstraction
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