Department of Information Systems and Analytics

ANLY 2300. Introduction to Data Analytics.

This course introduces fundamental data science and analytics concepts alongside their diverse practical applications. Students learn to use visualization software while exploring the essential mechanics of data wrangling, descriptive, predictive, and prescriptive analytical models. The curriculum also covers critical topics such as data governance and the significant societal implications of analytics. By focusing on the development of data storytelling, students learn to communicate effectively. This comprehensive approach ensures learners can navigate technical challenges while understanding the broader organizational landscape of modern data in a professional environment.

ANLY 2333. Business Statistics.

This course covers essential descriptive and inferential statistical techniques designed specifically for effective business and economic decision-making. Students explore key topics including measures of central tendency and dispersion, probability distributions, sampling distributions, and confidence intervals. The curriculum also delves into hypothesis testing, simple linear regression, and correlation analysis. By using these quantitative methods, students develop the ability to analyze data accurately and interpret statistical results within professional contexts. This foundational knowledge empowers students to make evidence-based decisions and solve organizational challenges efficiently. Prerequisite: [ISAN 1325 or ISAN 1323] and [MATH 1329 or MATH 2471] both with grades of "D" or better.

ANLY 3314. Decision Analytics.

This course introduces the theory, algorithms, and practical applications of decision-making methods used for analyzing and solving business problems. Students explore diverse quantitative approaches, including linear programming, integer programming, network optimization, and simulation. The curriculum also examines decision models designed to navigate uncertainty within professional contexts. By focusing on these analytical techniques, learners develop the skills necessary to model organizational systems and evaluate alternative strategies effectively. This foundation allows students to provide rigorous, data-driven support for critical management decisions within modern organizations. Prerequisite: ANLY 2333 or MATH 2328 or [ANLY 2300 and [GEO 3301 or PSY 2301 or IE 3320 or SOCI 3307 or PH 3315]] with a grade of "D" or better and a minimum 2.0 Overall GPA.

ANLY 3330. Introduction to Business Analytics.

This course introduces fundamental business analytics concepts alongside diverse practical applications. Students learn to use visualization software while exploring the essential mechanics of data wrangling and various analytical models. The curriculum also examines the ethical and societal implications of data usage within modern professional environments. By focusing on the development of data storytelling, students learn to communicate complex findings effectively. This comprehensive approach ensures learners can navigate technical challenges while understanding the broader organizational landscape of data-driven decision-making.

ANLY 3334. Statistical Modeling.

This course allows students to apply a broad range of statistical analysis techniques using software for business decision-making. Students explore essential topics including probabilistic simulation, general and generalized linear models, and time series forecasting. Significant emphasis is placed on model formulation, interpretation, and validation within real-world contexts. By focusing on these quantitative methods, learners develop the skills necessary to analyze complex datasets and support organizational objectives. This comprehensive approach ensures that students provide rigorous, data-driven insights. Prerequisite: ANLY 2333 or MATH 2328 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ANLY 3339. Data Mining and Visualization.

This course introduces fundamental data mining concepts and practical skills for applying advanced techniques to solve complex business problems. Students explore essential topics including data visualization, various analysis algorithms such as prediction, classification, clustering and corresponding performance metrics. Significant emphasis is placed on model assessment specifically for big data sets within professional contexts. By focusing on these quantitative methods, learners develop the ability to analyze large-scale information and interpret results effectively to support strategic, data-driven organizational decisions. Prerequisite: ANLY 2333 or MATH 2328 or [ANLY 2300 and [GEO 3301 or PSY 2301 or IE 3320 or SOCI 3307 or PH 3315]] with a grade of "D" or better and a minimum 2.0 Overall GPA.

ANLY 3341. Computational Methods for Analytics.

This course provides a comprehensive introduction to statistical programming, focusing on the use of programming tools and quantitative methods to analyze large datasets. Students explore key topics including the creation of graphs for statistical analysis, rigorous statistical modeling, and diverse visualization techniques. The curriculum also covers simulation and optimization methods essential for modern data analytics. By learning these programming skills, students develop the ability to process extensive information and derive meaningful insights to support evidence-based decision-making. Prerequisite: ANLY 2333 or QMST 2333 or MATH 2328 or [ANLY 2300 or QMST 2300 and [GEO 3301 or PSY 2301 or IE 3320 or SOCI 3307 or PH 3315]] with a grade of "D" or better and a minimum 2.0 Overall GPA.

ANLY 4320. Analytics in Practice.

This course covers the practical application of analytical methods within modern business practice. Students work on a comprehensive applied project encompassing critical stages: problem understanding, data preparation, model building, and validation. Significant emphasis is placed on the effective communication of findings to diverse stakeholders. By navigating the full analytics lifecycle, learners develop the skills necessary to transform raw data into actionable business decisions. This hands-on approach ensures students are able to successfully manage complex projects and provide data-driven solutions for real-world organizational challenges. Prerequisite: [ANLY 3334 OR ANLY 3339] AND [ANLY 3341 OR ISAN 3305] with grades of "D" or better and a minimum 2.0 Overall GPA.

ANLY 4321. Predictive Analytics.

This course covers the use of statistical learning methods, specifically focusing on regression and classification to solve business problems. Students explore feature selection and shrinkage techniques, including ridge and lasso regression. The curriculum also examines deep neural network learning, ensemble methods like bagging and boosting, and foundational concepts such as entropy. Throughout the course, the bias-variance trade-off is emphasized. By learning these sophisticated tools, students develop the ability to build predictive models that enhance strategic decision-making within organizational environments. Prerequisite: ANLY 3339 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ANLY 4373A. Operations Analytics.

This course introduces analytical methods and quantitative tools used in the planning, design, and management of business operations. The course integrates data-driven decision making with operational theory, emphasizing forecasting, service and queueing systems, optimization modeling, decision analysis, simulation, and quantitative supply chain analytics. Students examine real-world operational contexts such as inventory control, logistics and distribution planning, process and capacity analysis, and quality management. Through applied problem-solving and computational tools, the course develops analytical reasoning and practical modeling skills relevant to contemporary operations and supply chain environments. Prerequisite: A minimum 2.0 Overall GPA.

ANLY 4373F. Big Data Analysis and Artificial Intelligence.

This course covers the utilization of analytical and artificial intelligence methods alongside big data to solve complex business problems. Students explore high-performance computing, big data storage, and advanced analysis techniques. The curriculum introduces distributed and parallel programming designed to increase throughput and reduce latency for selected applications. By learning these sophisticated technologies, students develop the skills necessary to manage massive datasets and optimize computational efficiency. This foundation ensures students develop the abilities to provide high-speed, scalable solutions within modern, data-intensive organizational environments. Prerequisite: [ISAN 3305 OR ANLY 3341] AND ISAN 3382 AND ANLY 4321 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ANLY 4395. Independent Study in Analytics.

This course provides an in-depth, faculty-supervised study focusing on a selected analytics topic or a specific applied problem. Students conduct independent research or project-based analysis using advanced analytical methods and sophisticated technical tools. This rigorous exploration allows for the practical application of theoretical knowledge to unique business challenges. The course may be repeated once for credit, provided the student selects a different area of emphasis. By engaging in this supervised study, learners develop specialized expertise and professional-grade problem-solving capabilities. Prerequisite: Instructor Approval.

ANLY 4399. Analytics Internship.

This course provides a comprehensive integration of professional and academic experience through a structured internship with an external employer. Students apply knowledge to real-world business challenges within a professional organizational setting. This practical engagement fosters the development of essential industry skills while building valuable career networks. By completing this internship, students gain significant workplace insights that bridge the gap between advanced analytical studies and professional practice. Academic credit for this experiential learning opportunity is awarded on a pass/fail basis. Prerequisite: Instructor Approval.

ISAN 1323. Introduction to Microcomputer Applications.

This course develops advanced information technology skills, focusing on office productivity software. Primary emphasis is placed on spreadsheet, database, and presentation software. Advanced techniques are presented for use in data analysis and decision-making. Students will be expected to demonstrate mastery of these techniques in a hands-on environment. ISAN 1323 will not count towards a Pre-Business or Business Degree.

ISAN 1325. Introduction to Microcomputer Applications in Business.

This course develops information technology skills, focusing on office productivity software. Primary emphasis is placed on spreadsheet, database, and presentation software. Techniques are presented for use in data analysis and decision-making. Students will be expected to demonstrate mastery of these techniques in a hands-on environment. ISAN 1325 will only count towards a the Pre-Business curriculum and Business curriculum.

ISAN 3305. Business Programming I.

This course examines application program development, including requirements analysis, design, implementation, and testing. Structured and object-oriented programming concepts are used to develop solutions to business problems using a visual programming language. Students analyze business requirements and apply programming techniques to design and implement functional applications. Prerequisite: ISAN 1325 or ISAN 1323 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ISAN 3317. E-Business.

This course examines e-business concepts, technologies, and organizational applications in digital commerce environments. Students study technology infrastructure including mobile platforms, security protocols, and digital payment systems. Topics include online retail, social networks, digital marketing, business-to-business supply chain management, and collaborative commerce. The course also considers ethical, legal, and political issues associated with e-commerce operations. Students analyze business models, information systems, and strategies used to support electronic transactions and digital business activities across organizational settings. Prerequisite: A minimum 2.0 Overall GPA.

ISAN 3325. Business Programming II.

This course examines advanced application development concepts including user interface design, business logic, and data access within tiered architectures. Students apply object-oriented programming principles to develop applications using a modern development framework. Topics include classes, inheritance, graphical user interface programming, event handling, arrays, tables, and database programming. The course also examines structured data management, application functionality, and techniques for integrating user interfaces with data processing components in business application environments. Prerequisite: ISAN 3305 with a grade of "D" or better and a minimum 2.0 Overall GPA. Corequisite: ISAN 3374 and ISAN 3382 both with grades of "D" or better.

ISAN 3348. Data Communications and Network Architecture.

This course examines concepts of data communications and network design within computer networking environments. Using a systems approach, students study network management, implementation, and security. Topics include the OSI model, TCP/IP architecture, network protocols, wired and wireless local area networks, backbone networks, wide area networks, and enterprise networks. The course also covers Internet architecture, network hardware, network media, network security, and network management strategies. Students analyze and design network solutions for organizational and business communication needs. Prerequisite: A minimum 2.0 Overall GPA.

ISAN 3350. Information Systems Security.

This course examines the concepts of information systems and network availability, integrity, and confidentiality in order to develop effective security controls, processes, practices, and procedures. Topics include methodologies, models, architectures, access control systems, ethics, and legal implications of information technology security. Students examine how security principles are applied within organizational and regulatory contexts to support effective governance of information systems. Prerequisite: A minimum 2.0 Overall GPA.

ISAN 3360. Web Design and Development.

This course examines web design and development concepts used in contemporary web applications. Students develop skills in semantic HTML, CSS layouts, JavaScript programming, multimedia integration, and responsive web design. Topics include website structure, accessibility, mobile-responsive design, user interface development, and web content presentation across multiple devices. The course also covers techniques for integrating external resources, managing page functionality, and developing interactive web pages using current web development frameworks and standards. Prerequisite: A minimum 2.0 Overall GPA. Corequisite: ISAN 3374 with a grade of "D" or better.

ISAN 3374. System Analysis and Design.

This course examines the analysis and design phases of the Systems Development Life Cycle (SDLC). Students study techniques and tools for determining system requirements and developing logical design models using structured and object-oriented methodologies. Topics include requirements analysis, user stories, system architecture, user interface design, data modeling, and project documentation. The course also covers methods for translating organizational requirements into system specifications and design models used in information systems development. Prerequisite: A minimum 2.0 Overall GPA.

ISAN 3380. Enterprise Information Technology and Business Intelligence.

This course examines enterprise information technologies and business intelligence applications used in organizational environments. Students use integrated software applications to access, manage, and analyze business information from multiple sources. Topics include data analytics, database queries, reporting, data visualization, cloud computing, business continuity, cybersecurity, and decision support systems. The course also covers business processes, information quality, and the use of enterprise data in organizational analysis and managerial decision-making using contemporary information technologies. Prerequisite: [ISAN 1325 or ISAN 1323] and [ANLY 2333 or MATH 2328] and [MATH 1329 or MATH 2471] all with grades of "D" or better and a minimum 2.0 Overall GPA.

ISAN 3382. Computer Data Base Systems.

This course examines concepts and methodologies related to database planning, design, development, and implementation in organizational environments. Emphasis is placed on logical database design, relational database structures, and relational database management systems. Topics include relational query languages, Structured Query Language (SQL), advanced JOIN statements, nested subqueries, data manipulation, database views, and Data Definition Language (DDL). Students develop database applications and relational database structures used to support business information systems and organizational data management. Corequisite: ISAN 3305 or ANLY 3341 with a grade of a "D" or better.

ISAN 3389. Programming for Data Processing.

This course examines programming techniques used for processing numerical and textual data from external sources. Topics include sequence and collection structures, object serialization, reporting methods, data acquisition, data cleaning, and integration of multiple data sources. Students develop applications for processing structured and unstructured datasets using object-oriented programming concepts and modern software development techniques. The course also covers methods for analyzing, manipulating, and managing data within information systems and data-processing environments. Prerequisite: ISAN 3305 and [ANLY 2333 or MATH 2328] both with grades of "D" or better and a minimum 2.0 Overall GPA.

ISAN 3390. Agile Project Management.

This course examines project management concepts and practices used in information technology environments, with emphasis on Agile methodologies. Topics include project scope, scheduling, costs, quality, risk management, portfolio management, release planning, procurement, human resources, and international project considerations. Students study Scrum frameworks, backlog management, iterative development, and project management software used to support project planning and implementation. The course also addresses project coordination and organizational processes associated with Agile project management practices. Prerequisite: ISAN 3374 and ISAN 3305 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ISAN 3392. Introduction to Machine Learning.

This course provides a comprehensive overview of foundational concepts, algorithms, and applications of machine learning. Students gain hands-on experience through programming assignments and case studies, exploring real-world applications like natural language processing, computer vision, generative AI, and agentic AI. The course emphasizes both theoretical understanding and practical implementation of machine learning techniques, preparing students to apply these skills across various domains. Prerequisite: [ISAN 3305 or CIS 3305 or CIS 2324} and [ANLY 2333 or QMST 2333 or MATH 2328] with grades of "D" or better and a minimum 2.0 Overall GPA.

ISAN 4318. Object Oriented Development.

This course delves into the sophisticated application of object-oriented programming (OOP) principles within the realm of business application development. Topics include an in-depth exploration of concepts, methodologies, and toolsets essential for designing, implementing, and rigorously testing software applications grounded in the object-oriented paradigm. Participants will gain hands-on experience in applying OOP techniques to tackle real-world business challenges, ensuring a practical understanding of how these principles can be effectively utilized to build robust, scalable, and maintainable software solutions. Prerequisite: ISAN 3374 with a grade of "D" or better and a minimum 2.0 Overall GPA. Corequisite: ISAN 3382 with a grade of "D" or better.

ISAN 4321. Mobile Application Development for Android.

This course introduces the concepts, methodology, and toolset for designing business applications for mobile devices. Students will learn the MVC development framework and Java programming environment for Android to create interactive business applications. Prerequisite: ISAN 3374 with a grade of "D" or better and a minimum 2.0 Overall GPA. Corequisite: ISAN 3382 with a grade of "D" or better.

ISAN 4322. Computer System Development and Design.

This course integrates systems development with analysis, design, project management, and the systems development life cycle. Object-oriented methods and UML models will be used to develop a project for a client. Students will select methodology, platform, and development technology based on client requirements. Prerequisite: ISAN 3325 with a grade of "D" or better.

ISAN 4325. Legacy Systems: Applications, Development, and Support.

This course examines the development, maintenance, support, and migration of legacy applications within organizational information systems environments. Topics include legacy programming languages, application development processes, testing procedures, troubleshooting methods, and application migration practices. Students study legacy enterprise systems, transactional processing environments, and software support operations using contemporary and legacy computing platforms. The course also addresses application portfolios, system documentation, maintenance strategies, and tools used to support legacy system development and organizational information technology operations. Prerequisite: ISAN 3305 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ISAN 4328. Artificial Intelligence: Development and Application.

This course examines Large Language Models (LLMs), Generative Pre-trained Transformers, and artificial intelligence application development. Topics include transformer architectures, model training, fine-tuning methods, text generation, neural translation, conversational systems, and model deployment practices. The course also addresses bias detection, safety considerations, model interpretability, ethical issues associated with artificial intelligence systems, and evaluation methods used in machine learning applications. Students develop and evaluate AI applications using contemporary machine learning frameworks and programming environments. Prerequisite: ISAN 3305 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ISAN 4332. Enterprise Resource Planning Systems.

This course examines enterprise resource planning (ERP) systems used to integrate business functions through shared organizational databases and information systems. Students study methodologies and tools associated with ERP system selection, implementation, and management. Topics include business process modeling, master data management, procurement, production, accounting, and business intelligence applications. The course also addresses enterprise information management, organizational workflows, and the use of ERP systems to support coordination, reporting, and operational processes within organizational environments. Prerequisite: ISAN 3380 with a grade of "D" or better.

ISAN 4349. Advanced Database Management Systems.

This course introduces advanced cloud-based database concepts and processes to support applications for Business Intelligence. Multi-dimensional modeling along with database, ETL (Extract, Transform, Load) & data pipeline, reporting, and advanced analytic capabilities of a modern database in a cloud-based environment will be used to design and develop objects, scaling, partition, storage optimization & cost management and multi-dimensional information cubes. Prerequisite: ISAN 3382 with a grade of "D" or better. Corequisite: ANLY 3339 with a grade of "D" or better.

ISAN 4350. Ethical Hacking.

This course examines the critical technology and managerial issues related to information security, with a specific emphasis on offensive security methodologies. Students explore the full lifecycle of a cyberattack, including sophisticated attack vectors, information gathering, enumeration, and systematic privilege escalation. It balances these offensive tactics with essential defensive security strategies, such as malware detection, firewall configuration, and incident response. Through hands-on exercises, students develop the technical proficiency required to identify vulnerabilities and implement robust disaster recovery plans, ensuring comprehensive protection for organizational assets in an increasingly hostile digital landscape. Prerequisite: Minimum 2.0 overall GPA and ISAN 3348 with a grade of a "D" or better.

ISAN 4358. Network and Cloud Administration.

This course examines the roles and responsibilities of network and cloud administrators in organizational environments. Topics include network operating systems, cloud service administration, server management, virtualization, and network security. Students analyze administrative practices used to configure, manage, and maintain enterprise network and cloud infrastructures commonly used in modern business organizations. Prerequisite: ISAN 3348 with a grade of "C" or better.

ISAN 4360. Developing AI Solutions for the Enterprise.

This course examines the design, development, and deployment of artificial intelligence solutions in enterprise environments. Students apply AI concepts and development methodologies to integrate models and services within tiered architectures that support organizational business processes. Emphasis is placed on evaluating how AI-enabled systems are implemented to address operational and decision-making needs within enterprise contexts. Prerequisite: ISAN 3374 and ISAN 3382 and [ISAN 3325 or ISAN 3392 or ISAN 4328] with a grade of "D" or better.

ISAN 4373A. Cyber-Warfare: Actors, Techniques, and Impact.

This course examines historical cyber warfare incidents involving nation-state actors with emphasis on offensive techniques and global impacts. Students analyze geopolitical, technical, and organizational factors associated with cyber operations, including network intrusion methods and operational timelines. The course also examines strategic consequences for organizations and international security systems through analysis of documented cyber warfare cases. Students evaluate attribution challenges, state-sponsored cyber conflict, and organizational responses to cybersecurity threats in contemporary global contexts. Prerequisite: A minimum 2.0 Overall GPA.

ISAN 4373D. Artificial Intelligence in Business Operations.

This course examines the application of artificial intelligence in business operations. Students analyze foundational AI concepts, including machine learning, natural language processing, and computer vision, and evaluate their use in areas such as marketing, finance, and operations. Through case studies and applied exercises, students assess how AI technologies support organizational decision-making and operational efficiency within contemporary business environments.

ISAN 4373E. Programming for Information Security.

This course covers advanced programming topics with a focus on information security. Students learn to develop secure software, identify and mitigate vulnerabilities, and apply coding for cybersecurity tasks. Utilizing practical examples and real-world scenarios, learners gain hands-on experience in crafting solutions to protect against cyber threats. Designed for those seeking to blend programming expertise with security best practices, this course equips participants with the skills to address contemporary digital security challenges. Prerequisite: CIS 2324 or CIS 3305 with a grade of "D" or better and a minimum 2.0 Overall GPA.

ISAN 4373F. Agentic Artificial Intelligence Development for Business Applications.

This course introduces the emerging field of agentic artificial intelligence and its applications in business. Students examine how intelligent agents operate within defined objectives, constraints, and human oversight to support organizational goals in areas such as decision support, operations, and customer engagement. The course emphasizes both the opportunities and limitations of developing systems that exhibit goal-directed behavior while remaining governed by business and technical controls. Through case studies and applied projects, students analyze how agentic approaches may influence business practices. This course does not earn graduate degree credit. Prerequisite: ISAN 3374 and ISAN 3382 and [ISAN 3325 or ISAN 3392 or ISAN 4328] all with a grade of "D" or better.

ISAN 4395. Independent Study in Information Systems.

This course provides faculty-supervised study of a selected information systems topic or applied problem. Students conduct independent research or project-based study within the information systems field and apply theoretical concepts to organizational or technical issues. Areas of emphasis vary according to student objectives and faculty approval. The course may be repeated once for credit when a different topic or project area is selected. Students document and present findings related to the approved area of study. Prerequisite: Instructor approval.

ISAN 4399. Information Systems Internship.

This course provides supervised internship experience with an external organization in an information systems-related setting. Students apply academic knowledge to organizational tasks, projects, and operational activities while examining professional practices within workplace environments. The course includes structured reflection connecting internship experiences to information systems concepts, ethical considerations, communication practices, and program learning objectives. Students document and evaluate workplace activities through faculty-guided assignments or reports. Academic credit is awarded on a pass/fail basis according to departmental internship requirements, employer evaluations, and institutional procedures. Prerequisite: Instructor approval.