Explores how information technology helps to achieve competitive advantage and improve decision making, business processes, operations, and organizational design. Uses a cross-functional perspective to recognize the role of technology across business activities of management, finance, marketing, human resources, and operations.

Explores how information technology helps to achieve competitive advantage and improve decision making, business processes, operations, and organizational design. Uses a cross-functional perspective to recognize the role of technology across business activities of management, finance, marketing, human resources, and operations.

Explores how information technology helps to achieve competitive advantage and improve decision making, business processes, operations, and organizational design. Uses a cross-functional perspective to recognize the role of technology across business activities of management, finance, marketing, human resources, and operations.

Programming skills for creating easy-to-maintain systems for business applications. Object-oriented and structured methodologies with Python.

Basic computer terminology, hardware and software, communications technology, graphics, systems analysis and design, and issues arising out of the rapidly evolving field of information systems. Students are expected to achieve a working knowledge of personal computer software, including operating system software and environments, as well as spreadsheets, analytical graphics, databases, and presentation software. Hands-on experience with the Internet and use of electronic mail.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

Beginning and intermediate topics in data modeling for relational database management systems.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. Transfer credit is awarded for work in an affiliated studies program.

Concepts and practices of information systems. Advanced programming techniques used to generate menu-driven applications.

This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office or the school's BBA Exchange Programs. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence.

Students apply skills in their major area and focus on additional project management skills through group projects conducted in a professional setting. Students may work with a private or a public enterprise.

Focus on data analysis using the Python programming language. Explore machine learning tasks such as classification and clustering.

Learn how information technology is used to coordinate supply chain activities across different industries.

Explore key management challenges and how data may be leveraged to guide decisions and improve operations, with the unifying theme of providing health care services in a manner that leads to lower cost and higher quality.

Introduction to data mining problems and tools to enhance managerial decision making at all levels of the organization. Discuss scenarios, including the use of data mining to support customer relationship management (CRM) decisions, decisions in the entertainment industry, financial trading, and even professional sports teams.

Introduction to social network analysis for business value using statistical optimization and decision theory. Analyze online search and conversation data for market sensing, sentiments, product quality, reputation, recommendations, and brand awareness.

Use data-driven tactics and strategies to predict consumer demand and optimize price and capacity/inventory availability to maximize revenue or profit. Explore demand analytics and revenue management techniques, produce rigorous and practical insights, and develop data analysis and optimization skills, based on business cases, datasets, and exercises. Examine diverse contexts and industries, such as conventional retailing, e-commerce, airline/hotel, and contemporary platform and cloud services (e.g., Uber, Dropbox, Netflix, AWS), by utilizing software (Excel, R, or Python) to build models, conduct optimization, and develop insights for a variety of revenue management examples.

Focus on a gamut of questions ranging from strategic to operational matters pertaining to a firm's social media initiatives, metrics to capture relevant outcomes, and predictive analysis to link social media chatter to business performance.

Explore mobile and web services technology models and architectures.

Provides foundation in business system analysis, project management, planning, design, and implementation using basic business knowledge and computer skills.

Designed to develop an understanding and appreciation for the role of information technology in the context of a firm's strategy. Explores the impact of information technology on the economy and business performance, the emergence of electronic business applications and organizational and market transformation, and the nature of technology-driven business models and strategies.

Selected topics in organizational communication, written and oral.

Communicating effectively in business using advanced writing and presentation concepts and techniques to increase individual and team effectiveness.

Explore designing, building, and implementing a relational database to improve company operations and reporting. Examine how databases affect analytics and app development.

Understanding, designing, and controlling the information processing activities of an organization. Complements Business Administration 380C by focusing on information systems rather than information technology. Includes business intelligence, knowledge management, data modeling, group decision support systems, and electronic commerce.

Emerging technology, data and process modeling (flow focus for integrated applications), reengineering, and change management.

Explore programming skills for creating easy-to-maintain systems for business applications. Examine object-oriented and structured methodologies with Python.

Selected topics in information technology and management of information systems development.

Project-oriented course focusing on implementation of organizational change.

The responsibilities of the strategist for choosing, developing, and managing an overall e-business firm strategy in uncertain market, technology, and policy environments.

Analysis of case studies, incorporating Oracle and other Web-based distributed computing solutions.

Discussion and hands-on use of current Web and distributed computing security software and e-forensic solutions.

Overview of research methods used to study information systems problems. Fundamental concepts and criteria for use with and evaluation of quantitative and qualitative, positivist and interpretive research methods. Current state-of-the-art applications.

Analyzes the competitive dynamics of platform-mediated networks; explores innovations like cloud computing in supporting network-based competition, the implications of information technology-enabled global sourcing, and business intelligence for business value and competitive advantage; and discusses the role of information technology in business transformation and making a case for information technology investments.

Explore general database concepts such as E-R modeling, relational database design, and advanced SQL. Design and develop mission-critical web-based business applications using databases. Explore data warehouse design and advanced analytics functions within SQL.

Analyze the competitive dynamics of platform-mediated business models; explore innovations such as cloud computing and Internet of things in supporting platform-based competition; study the implications of information technology-enabled disruption; understand applications of artificial intelligence and machine learning to develop competitive advantage; and discuss the role of information technology in business transformation.

Discuss artificial intelligence (AI) and machine learning (ML) through a review of AI and ML concepts, tools, and the complete AI/ML lifecycle in the context of tackling business and organizational challenges.

Explore modern data management practices, with a strong focus on design and implementation of scalable, cloud-native data systems. Learn to manage diverse data types--structured, semi-structured, and unstructured--across their full lifecycle. Examine the role of cloud infrastructure in enabling agile, secure, and scalable data solutions.

Focuses on the management of disruptive technologies, including analyzing whether an emerging technology is sustaining or disruptive, identifying new markets for disruptive technologies, justifying investments in disruptive technologies, implementing disruptive technologies, and appropriating value from them.

Project-oriented course focusing on design of organizational change.

Data modeling and information management for investment analysis and financial systems.

Explores foundations of business analytics related to database management, data analysis techniques, and business decision making to solve a business problem of a client.

An introduction to social network analysis for business value using statistical optimization and decision theory, including the foundation for analyzing online search and conversation data for market sensing, sentiments, product quality, reputation, recommendations, and brand awareness.

An introduction to basic concepts, methodology, algorithms, and technology used in business analytics and decision making. Explore concepts from probabilistic modeling, analysis and experimental design. Examine the basics of modern regression and classification, clustering, visualization, dimensionality reduction, A/B Testing and an introduction to deep learning.

Explore an introduction to fundamental concepts, methodology, algorithms, and technology used in business analytics and decision making covering the most powerful concepts and algorithms from probabilistic modeling, analysis and machine learning.

Focus on digital innovation in the healthcare industry that is driven by advances in information technology and artificial intelligence. Learn about different types of IT-enabled innovations that are revolutionizing healthcare delivery, develop technology-enabled strategies to enhance innovation, and evaluate how new types of AI-enabled innovations create value for patients and other stakeholders.

Theory and tools that support the design and implementation of balanced scoreboard evaluation systems.

Examine frameworks for understanding how to transform supply chain strategy in the face of pressures from technological, social, and political disruption.

Topics in management of information in specific industries or application areas.

Examines innovation-based business strategies that rely on internal and external sources, processes in different organization forms, and market structures.

Selected topics in business analytics.

Overview of hardware and software life cycles; in-depth considerations of program design, including experience programming for large-scale computer systems in COBOL, FORTRAN, and/or BASIC.

Introduction to artificial intelligence (AI) and machine learning (ML) through a review of AI and ML concepts, tools, and the complete AI/ML lifecycle in the context of tackling business and organizational challenges.

Selected topics in information technology and management.

Explore a range of subjects required for developing modern applications that operate over vast data sets that are potentially distributed in nature. Consider alternative technologies and architectures for working with big data, examining the pros and cons of the different approaches.

Generate business and social insights from user-generated content (e.g., text, images, video, etc.) through the use of text analytics, sentiment analysis, visualization techniques, etc.

Examine a variety of data mining and machine learning techniques for descriptive, predictive and prescriptive analytics. Explore approaches to analyzing different types of information from the Web (web structure, content, usage).

Design new healthcare solutions using emerging information technologies such as Internet of Things, cognitive computing, artificial intelligence, the cloud, mobile, and 3D and 4D printing.

Build a strong business and technical foundation for blockchain. Discuss business inefficiencies that can be addressed by blockchain technology. Examine cryptology and distributed computing that blockchain systems rely on, including an overview of Bitcoin. Explore current research problems, perform programming assignments, lead discussions, and hear presentations from industry and academic researchers.

Cover the development of the bitcoin protocol from scratch. Explore basic libraries to build the protocol using a step-by-step approach. Examine the primary and secondary aspects of scaling, mining and operating a bitcoin protocol based system.

Generate business and social insights from user generated content (e.g., text, images, video, etc.) through the use of text analytics, sentiment analysis, visualization techniques, etc.

Explore the mathematical foundations of AI including probability theory and linear algebra, concepts necessary as foundational knowledge for other AI related courses in program.

Learn fundamentals of modern cloud native applications, including how to design, develop, and operate them, as well as distributed programming fundamentals. Examine machine learning design patterns for big data and distributed programming concepts.

Explore how modern enterprises can harness the combined power of GenAI and traditional unstructured data analytics to unlock business value. Learn a broad range of business questions and analytics driven use cases, spanning decision-making, process optimization, and innovation.

Examine information technology-enabled digital transformation and explore how digitalization impacts firm competition and enables industry transformation. Learn the role of digital business models, how firms can compete in disruptive ecosystems, to think critically about the benefit and challenge of strategic AI implementations and change management in real-world applications.

Explore all aspects of the Internet of Things (IoT) product life-cycle. Interface with the devices (sensors/actuators) that collect data and affect the environment. Explore network protocols for communication with these constrained devices. Examine programming of the back-end services that host, manipulate and disseminate the collected data. Study the development of apps that facilitate human interaction with these devices and the analysis of the data they produce. Examine security, privacy and performance considerations specific to IoT.

Explore how to govern and control the complex cybersecurity, privacy, and IT risk organizations face in an era increasingly shaped by artificial intelligence (AI) and intelligent automation technologies. Discuss privacy-enhancing technology and ethical decision-making framework that help address the novel challenge posed by intelligent systems.

Explore how to design and deploy artificial-intelligence (AI) capability across the enterprise, including mapping AI solutions to specific business requirements and align them with strategic goals. Learn how to identify, assess, and prepare high-quality data essential for AI success and how to select and scale a suitable model and integrate with existing systems and processes. Examine governance and continuous-improvement practices that keep AI initiative reliable and effective over the long term.

Explore a basic working knowledge of the latest algorithms, business applications and limitations of what data science and AI can accomplish. Learn about attention mechanism and the transformer, image and language embeddings, large language models, multi-modal models, and the important latest idea in reasoning, as well as some of the key emerging issues in security and reliability.

Learn about state-of-art Generative AI (GenAI) models for image, video and language generation and how they are used in a business setting. Explore their architecture and mathematical foundation. Learn about machine learning models for decision-making.

Explore the emerging discipline of managing data products designed to power GenAI applications. Learn how to curate, package, and deliver reusable datasets and APIs optimized for retrieval-augmented generation, synthetic data generation, and LLM prompt engineering. Examine fitness for use, economic value, and continuous improvement of data assets.

Apply data governance framework to ensure the integrity, transparency, and fairness of GenAI system. Learn how to embed observability into AI workflows--tracking provenance, bias, quality metrics, and access rights across the AI lifecycle. Connect the socio-technical principles of data governance with the operational reality of GenAI to implement trust-by-design practices within enterprise AI programs.

Examine emerging security and privacy vulnerability in AI systems, with a focus on human manipulation vectors: prompt injection, phishing via AI-generated content, identity spoofing, and malicious feedback loops. Learn how adversaries exploit both model behavior and user trust, and how to counteract the risk through red teaming, user training, behavior-aware safeguards, and ethical AI design. Evaluate human-AI interaction security and apply layered defense that reinforce public trust in AI systems.

Investigate the technical foundation of cybersecurity, with a particular focus on an emerging threat and challenge at the intersection of cybersecurity and artificial intelligence (AI). Explore how AI functions both as an enabler of a cyberattack and as a vulnerable target, requiring robust security defenses.

Learn advanced programming and foundational software engineering concepts essential for developing robust, scalable web applications through practical, hands-on exploration using a traditional approach. Emphasis is on mastering the most popular full-stack framework, while reinforcing critical topics such as source code management, agile methodology, the software development life cycle (SDLC), and common design patterns.

Explore the prevention and mitigation of data security and privacy risks in newly designed digital artifacts through IT governance, risk, and control frameworks as well as relevant laws, regulations, and industry standards.

Develop real-life business and social solutions using emerging information technologies. Engage with industry partners to explore business context for IT Capstone projects.

An overview of convolutional neural networks, recurrent neural networks and generative adversarial networks. Explore deep learning and artificial neural networks. Applications include computer vision, image and time series modeling as well as computational aspects of deep learning over big datasets. Utilize Python and Tensorflow, among other tools.

Explore the strategic management of new IT-embedded product and service innovations and their incorporation into the digital business ecosystems of organizations.

Examine the role of Information Technology in managing Supply Chains. Explore the IT capabilities needed by firms to coordinate their operations, collaborate with business partners and manage uncertainty. Illustrate the role of technologies and tools like ERP platform, ABAP programming, XML, web services, distributed computing and machine learning to improve the performance of supply chains.

Utilize design tools and methods to understand user needs, frame business opportunities, and design solutions. Examine design from both organizational and technical perspectives. Conduct research with end users, synthesize data, prototype solution ideas, and communicate compelling stories. Undertake design challenges that focus on emerging information technologies, including the internet of things (IoT), cognitive computing, AI, cloud, mobile, and 3D/4D printing.

Explore various approaches to modern app development, including required advanced programming and software engineering concepts. Explore approaches to app development ranging from native platform programming through programming frameworks that allow cross-platform development, to high-level approaches based on web frameworks.

Preparation of a report to fulfill the requirement for the master's degree under the report option.