Online Master of Science in Information Systems

Foundations in Accounting

This course educates students in the fundamentals of finance and accounting. The methods covered are used extensively throughout the MBA program. Topics include: the accounting process that results in the preparation of financial statements for external users, techniques for analyzing a basic set of financial statements, using accounting information to support management decisions, and using time value of money techniques to evaluate capital asset decisions. (MS Accounting students cannot earn credit by taking this course.) This course cannot be used as an elective course for Lindner College of Business Master's programs.

Data Analysis

Introduction to data analysis and statistical methods with focus on practical decisions using quantitative models in a spreadsheet environment. Topics include sources of data, descriptive and graphical statistical methods, probability, distributions, sampling and sampling distributions, estimation, confidence intervals, and hypothesis testing. This course may not be used as an elective course for Lindner College of Business Master's programs.

Foundations in Finance

Upon completion of this course, students should be able to: 1. Apply concepts and perform Time Value of Money calculations 2. Understand differences in interest rates (due to differences in risk, horizon, and compounding) 3. Use present value calculations to solve bond pricing and risk applications 4. Use present value calculations to solve stock valuation applications This course cannot be used as an elective course for Lindner College of Business master's programs.

Information and Technology Management

This course employs the case method to discuss the managerial and strategic implications of the use of Information Systems in organizations. The course starts with a review of concepts related to Information Technology in the realm of networking,databases, application development, and architecture. Next, it examines the value of Information Technology in modern organizations. Finally, multiple cases are discussed, covering themes like Enterprise Resource Planning, Digital Convergence, e-Marketing and Social Media, Disruptive Innovations, Virtual Teams, and IT Resources and Capabilities.

Marketing Foundations

The purpose of this course is to provide students with a foundation in Marketing. Concepts such as segmentation, targeting, positioning, customer and market analysis, and basic marketing planning will be introduced. This course cannot be used as an elective for Linder College of Business master's students.

Programming and Modern Frameworks

This course introduces full-stack development, emphasizing modern programming languages, frameworks, and best practices for building scalable, high-performance web applications. Through hands-on projects, students will develop real-world applications that integrate both front-end and back-end technologies. By the end of the course, students will have built and deployed a fully functional web application using contemporary frameworks and cloud-based deployment strategies.

Systems Analysis and Design

There is no activity more fundamental to the field of information systems (IS) than the analysis, design, and development of systems. In this course, students will learn to analyze and document the requirements for a system, using two distinct approaches to process modeling. The first of these is BPMN (Business Process Modeling Notation) - a technique that is quickly becoming the standard for business process modeling. The second is an Object Oriented approach, using UML (Unified Modeling Language) - specifically, students will learn to draw use-case diagrams, class diagrams, and sequence diagrams.

Integration with Cloud Systems

This course provides a comprehensive introduction to cloud-based application integration and modern API-driven architectures. Students will explore cloud computing fundamentals, focusing on how cloud servers interact with enterprise applications through RESTful APIs, microservices, and cloud-native technologies. The course covers authentication mechanisms, API gateways, serverless computing, and containerization to optimize application scalability and efficiency.

Data Modeling

This course provides in-depth coverage of the principles of data modeling. Starting at the highest level of abstraction, the data requirements culled out from user requirements specification are rendered as a conceptual data model using Entity-relationship modeling grammar. Students then learn how to map the conceptual model to the logical tier using relational modeling grammar, in preparation for the ultimate database design. Workshop sessions are included to provide students hands-on modeling opportunities. A basic introduction to Structured Query Language (SQL) is also included.

Database Systems

This course provides a comprehensive introduction to data modeling and database design, covering the full process from conceptual modeling to database implementation. Students will learn to analyze user requirements and develop Entity-Relationship (ER) models, map them to relational models, and apply normalization techniques to refine database structures. The course also covers Structured Query Language (SQL) for data definition (DDL), data manipulation (DML), and data control (DCL). Through hands-on workshops and lab sessions, students will gain practical experience in database normalization, optimization, and query development to design and implement efficient, scalable database solutions for real-world applications

Data Warehousing and Business Intelligence

This course is designed for the comprehensive learning of data warehousing technology for business intelligence. Data warehouses are used to store (archive) data from operational information systems. Data warehouses are useful in generating valuable control and decision-support business intelligence for many organizations in adjusting to their competitive business environment. This course will introduce students to the design, development and operation of data warehouses. Students will apply and integrate the data warehousing and business intelligence knowledge learned in this course in leading software packages.

Data Mining for Business Intelligence

This course is designed for the in-depth learning of data-mining knowledge and techniques in the context of business intelligence. The topics include association rules, classification, clustering and text mining. Students will apply and integrate the business intelligence knowledge learned in this course in leading software packages.

Enterprise Resource Planning 1

Enterprise Resource Planning (ERP) Systems are large, cross-functional systems designed to promote integration among the various business areas. While there are many ERP systems, SAP has, by far, the highest market share. An important step in implementing SAP is configuration, which involves selecting options in SAP to align with the specific requirements of the business. This course is a hands-on introduction to SAP configuration. Specifically, students will go through the process of setting up a small trading company on SAP, including setting up the organization structures, master data, and rules; and processing transactions to test the setup. The course covers three SAP modules - FI, MM, and SD.

IS Project Management

This course focuses on the management of IS projects, although many of the concepts examined also apply to other projects. Planning, organizing, staffing, and controlling projects require traditional management skills as well as an understanding of specific project management tools and techniques. This course starts with an overview of project management concepts. It then discusses project planning, monitoring, and controlling. It also covers the politics of projects, project staff, and teamwork issues. The Project Management Institute's "A Guide to the Project Management Body of Knowledge," along with current research and management trends related to IS project management, provide the framework for the material covered in this class. The course uses Microsoft Project for hands-on exercises.

IS Security

This course is an overview of the field of Information Security, Privacy, and Assurance. It introduces students to the key issues associated with protecting information assets, determining levels of protection and response to security incidents, and designing a consistent, reasonable information security system, with appropriate intrusion detection and reporting features. Topics covered in the course include: inspection and protection of information assets, detection of and reaction to threats to information assets, pre- and post-incident procedures, technical and managerial responses, and an overview of the Information Security Planning and Staffing functions.

Career Management

Designed for Graduate Business students to assist them in their job search. Covers such topics as your elevator speech, practice interviewing, resume construction and salary negotiations.

Industry Practicum 2

This course is associated with the experiential component of the MS-IS program. It is a follow on to IS 7090. The purpose of this course is to allow students to engage in longer and more complex projects (whether as part of a co-op/internship, or an independent project) that go beyond the scope of a single course (IS 7090).

Data Visualization

This course provides an introduction as well as hands-on experience in data visualization. It introduces students to design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making.

Statistical Computing

This is a course on the use of computer tools for data management and analysis. The focus is on a few popular data management and statistical software packages such as SQL, SAS, SPSS, S Plus, R, and JMP although others may be considered. Data management and manipulation techniques including queries in SQL will be covered. Elementary analyses may include measures of location and spread, correlation, detection of outliers, table creation, graphical displays, comparison of groups, as well as specialized analyses.

Data Wrangling

This course provides an intensive, hands-on introduction to data management and data manipulation. You will learn the fundamental skills required to acquire, munge, transform, manipulate, and visualize data in a computing environment that fosters reproducibility.

Data Analysis Methods

This course covers the fundamental concepts of applied data analysis methods. Various aspects of linear and logistic regression models are introduced, with emphasis on real data applications. Students are required to analyze data using major statistical software packages. BANA 7038 should not be taken for credit by MS-Business Analytics students.

Enterprise Resource Planning 2

This course is a follow on to IS 7050. Students will continue their study of SAP configuration, focusing on the CO and PP Modules. Specifically, students will set up the organization structures, master data, and rules needed to run a manufacturing company on SAP, and process transactions to test the setup.

Advanced Web Development with .Net

This course is a follow on to IS 7012 and uses the.Net framework introduced in that course to explore advanced topics. Specific topics covered in the course include: advanced programming techniques in C# to manipulate classes and tables,the creation and use of AJAX controls in .Net web applications, Dynamic Data web sites, and the MVC framework, including how to create a database-bound web application following the MVC pattern.

Big Data Integration

This course presents an overview of the principles of data integration, the fundamental basis for developing useful and flexible business intelligence platforms. Modern data integration needs differ from traditional approaches in four main dimensions that parallel differences between big data and traditional data: volume, velocity, variety, and veracity.

Enterprise Architecture

Enterprise Architecture represents the structure and operation of an organization to effectively and efficiently achieve its current and future business objectives. This course is designed to expose the student to the elements of Enterprise Architecture and to the roles and necessary skills required by the Enterprise Architect. It is a combination of theory and the practical, but the emphasis and focus will be on the practical. The problems addressed are real-world problems currently faced by organizations.

CIO Forum

As an IS professional, the ultimate accomplishment is often to become the CIO of a major corporation.In this course CIOs and their associates will share their perspectives on what makes a successful CIO in an enterprise. A particular focus of the course will be strategic and operational aspects of a CIO's job. Time will be spent on the challenges, opportunities, environmental factors, organizational dynamics and other aspects that are incorporated as part of the CIOs leadership and operational responsibilities. Students will also be educated on how practices and approaches differ based on leadership styles, company operating principles, corporate culture, and inherent aspects of industry segments. The course will include presentations by various CIOs, business leaders, entrepreneurs and partner company leaders that comprise the ecosystem of the larger operating framework. The course will also address IT Career Perspectives from the viewpoint of industry thought leaders. How did successful CIOs get there? What are some of the career choices they made, and why? It is an opportunity for students to learn from senior executives, thus bridging the gap between theory and practice in IT.

Supply Chain Strategy and Analysis

Presents an overview of issues relating to the design and operation of an organization's supply chain. Information is presented as a mix of technical models and applied case studies. Topics may include inventory planning, logistics, sustainability, global operations, supply chain collaboration and contracting.

Survey of Machine Learning and Artificial Intelligence

This course is a survey of Machine Learning (ML) and Artificial Intelligence (AI) from the Data Scientist’s perspective. It explores ML and AI topics, current and emerging technologies, and applications for students to gain understanding of the successful implementation of ML and AI to address key business and industry problems.

Data Mining I

This is a course in statistical data mining with emphasis on hands-on case study experiences using various data mining/machine learning methods and major software packages to analyze complex real world data. Topics include data preprocessing, k-nearest neighbors, generalized linear regression, subset and LASSO variable selection, model evaluation, cross validation, classification and regression trees.

Machine Learning Design for Business

This course provides a framework for developing real-world machine learning systems that are deployable, reliable, and scalable. Designing machine learning systems is the process of defining the software architecture, infrastructure, algorithms, and data for a machine learning system to satisfy specified business requirements. Without deliberate design, machine learning systems can get outdated quickly because (1) the tools continue to evolve, (2) business requirements change, and (3) data distributions constantly shift. Students will learn about data management, data engineering, feature engineering, approaches to model selection, training, scaling, and how to continually monitor and deploy changes to ML systems for successful business applications. They will also be exposed to managing the human side of ML projects such as team structure and business metrics.

Special Topics in Information Systems

This course is used to explore topics of current interest in the IS domain, that do not fall within the scope of any of the regularly scheduled courses. By the very nature of the course, specific topics covered will vary with each offering.

Governance of AI/ML Systems

This course teaches students how to develop, scale-up, and sustainably manage high-performing Artificial Intelligence/Machine Learning systems in business organizations. It introduces concepts and techniques that enable the development of surrogate approaches to explain AI/ML models, build redundancy in AI/ML systems, and calculate and minimize risk of failures while using such approaches.

Generative Artificial Intelligence for Business

This course examines the technology underlying modern generative artificial intelligence / machine learning models from a business perspective, including their uses in coding, professional and artistic applications, and the various controversies and challenges to work and/or society they may pose.

Survey of Machine Learning and Artificial Intelligence

This course is a survey of Machine Learning (ML) and Artificial Intelligence (AI) from the Data Scientist’s perspective. It explores ML and AI topics, current and emerging technologies, and applications for students to gain understanding of the successful implementation of ML and AI to address key business and industry problems.

IS Compliance and Policy

Information systems are embedded in all aspects of an organization's operations. Thus, the need to assess the risks and evaluate the controls over these systems is becoming increasingly vital to the organization, its customers, and society at large. This course acquaints students with tools and techniques to determine whether an organization's information systems are adequately protected, monitored, and have controls in place to meet legal requirements. Students will also learn how to build adequate controls in the systems they develop.