The Virginia Tech's Master of Information Technology (VT-MIT) interdisciplinary degree and graduate certificate program offers courses from both the Pamplin College of Business and College of Engineering. Courses span diverse technology disciplines such as business data analytics, AI/ML, cybersecurity, networking, and software development. The flexible curriculum allows you to design a degree that supports your technical growth in these career-focused subjects while also helping you build the strategic leadership foundation you need to prepare for the next stage of your career.
The Master of Information Technology degree comprises of 11 courses—four core courses and seven elective courses—for a total of 33 credit hours.
Students pursuing the Master’s degree on a part-time basis commonly finish in 2.5 years, while full-time students can finish in 15-18 months. The maximum time to finish the degree is five years. Courses are offered in a traditional semester format – about 15 weeks fall/spring and 12 weeks in summer terms.
Course descriptions of our Core and Elective offerings and degree planning documents are available below to help you design the degree to your needs.
You must select four core courses. If you wish to take more than four core courses, the additional core courses will count as electives.
This course is an introduction to design methodologies in information systems. Structured systems analysis and design methodologies are discussed. An introduction to database design methodologies is also included. Topics related to different database models and their implementation is discussed. Students are also required to design and implement information systems using appropriate computer software.
An examination of the concepts, technologies, and applications of electronic commerce. Topics include the World Wide Web as a platform for electronic commerce; intranets; electronic data interchange; electronic banking and payment systems; security and firewalls; software agents; and the social, legal, and international issues of electronic commerce.
Object-oriented programming concepts and the Java programming language. The application of design strategies, notations, and patterns related to object-oriented systems. Techniques and libraries for developing applications related to the World Wide Web. Prerequisite: Proficiency in a high-level programming language (C, C++, C#, or Java), practical training and/or work experience related to developing computer software and systems.
Study of the principles and tools applicable to the methodical construction and controlled evolution of complex software systems. All phases of the life cycle are presented; particular attention focuses on the design, testing, and maintenance phases. Introduction to software project management. Attention to measurement models of the software process and product that allow quantitative assessment of cost, reliability, and complexity of software systems. Prerequisite: CS 5044.
Fundamental principles and concepts of computer systems. Computer hardware, Boolean logic, number systems and representation design and operation of digital logic; analysis of instruction set architectures and computer organization, and specification of data communication and networking standards. Prerequisite: Proficiency in a high-level programming language (C, C++, C#, or Java), practical training and/or work experience related to developing computer software and systems.
This course focuses on the role of the leader in crafting corporate and business strategies where technology provides the basis for the firm's competitive advantage.
To complete the 11-course requirement of the degree, you must choose seven elective courses. View list of electives organized by topic areas.
This course relates database theories and practices to concepts from other areas such as programming languages, algorithms, data structures, and information systems. The relational, network, and hierarchical models are introduced. A major portion of the course deals with data manipulation languages for the relational model, design theory for relational databases and query optimization. Prerequisite: ACIS 5504.
Study of theoretical and pragmatic approaches to the development of computer-based information systems. The emphasis is on the management of the systems development process. Strategies for managing the complexity of information systems are explored. The building of logical and physical models of systems through traditional non-executable models and executable computer prototypes. Prerequsite: ACIS 5504.
Cybersecurity governance and risk management program in organizations. Governance frameworks for cybersecurity and external drivers for cybersecurity. Risk management, including existing frameworks, principles, and strategies related to risk assessment and implementation of cybersecurity policies, controls and procedures. Budgeting and evaluation of risk management programs. Compliance with organizational cybersecurity programs, including risks of insider threats, management of security-related personnel, and establishment of cyber hygiene. Cybersecurity governance in relation to cybersecurity regulation. Suggested prerequisite: BIT 5594 OR MGT 5804.
This course provides an in-depth investigation into the complex and evolving nature of security, privacy, and safety in cyberspace. Students traverse the cyber threat landscape and the motives, methods, and mechanisms that shape it. Coursework examines the consequences posed by cyber threats at the individual, corporate, national, and societal levels. Designed for students with diverse backgrounds and interests across technical, managerial, and policy aspects of cybersecurity. Suggested prerequisite: BIT 5594 OR MGT 5804.
Key legal, ethical, and policy cyber governance and cybersecurity topics for managers and information security officers. Legal rights, remedies, and limitations related to cybercrime, computer intrusion, national security, and data breaches. Privacy laws and standards, impact assessments, privacy and security by design as policy and legal requirements. Comparison of international approaches to relevant laws and policies. Fundamentals of managing legal and policy aspects of information technology and security. Suggested prerequisite: BIT 5594 OR MGT 5804.
This course covers the enterprise cybersecurity lifecycle from a managerial perspective. Coursework includes the design of a comprehensive and resilient enterprise cybersecurity program that aligns with a set of business objectives. Topics include establishing policies and managing resources; overseeing and running cybersecurity operations; assessing security posture and mitigating vulnerabilities, and responding to security threats and failures. Suggested prerequisite: BIT 5594 OR MGT 5804.
This course explains the characteristics, use, and development of decision support systems (DSS) within the context of other business information systems. The process of designing and implementing decision support systems in business is discussed from both theoretical and practical standpoints. Students will learn various ways of measuring the success of DSS implementation as well as the difficulties associated with all such measures. Students will learn to use common software tools to develop a simple DSS and will learn to use the Internet as a decision-making and productivity tool. Suggested prerequisite: BIT 5594.
Overview of business intelligence and analytics technologies and their strategic use including defining/framing the business context for decisions, decision models, data issues, business intelligence, building analytics capability, cloud computing, making organizations smarter, and measuring the value of analytics. Suggested prerequisite: BIT 5594 OR MGT 5804.
Development of business intelligence and analytics solutions and applications for various types of decision-making problems. Analytics software and techniques. Data preparation, data exploration and visualization, predictive analytics techniques, text analytics, and spatial analytics. Prerequisite: BIT 5524.
Use of information technology in the health care industry. Topics address electronic health records, patient informatics, evidence-based medicine, electronic prescribing and telemedicine and the use of these technologies to improve patient health and medical systems operations. Suggested prerequisite: ACIS 5504.
Organization and management of data in the health care industry. Includes standards for electronic health records, healthcare enterprise systems architecture, health database design, existing database platforms, data integration from multiple sources, database accessibility. Analysis of healthcare-related organizations from the perspective of multiple user groups including patients, technicians, nurses, physicians, clinics, hospitals and insurance companies. Suggested prerequisite: ACIS 5504.
Course Description: Through this course, students will be able to grasp the fundamental concepts of Generative AI, including strengths and weaknesses; recognize the potential applications in diverse business scenarios; design and implement a basic Gen AI application relevant to business operations; design solutions that benefit both technical and non-technical users; and cultivate skills for introducing and managing organizational change around AI adoption and projects.
Course Description: This course examines the current emerging technology business landscape and puts forth best practice mechanisms to utilize communications-related technologies to transform business operations. The course will provide exposure to global, national, and corporate constructs for ICT governance and emerging data analytics applications. Students will learn how standards bodies, industry associations, and other stakeholders impact the introduction of technical innovations. Students will also learn how Policy and Regulation shapes technology insertion in mature markets and critical infrastructure industries. The course will utilize a hybrid presentation model with both symmetric and asymmetric learning.
Languages and technologies needed to develop modern data-centric web applications. Commonly used protocols and standards. Client-side technologies such as HTML, CSS and JavaScript; server-side technologies such as Servlets and JSP, and database access with SQL. Principles and technologies for web application architecture, electronic commerce and web application security. Prerequisite: CS 5044.
This course covers languages and technologies needed to develop applications for modern mobile devices. Students discuss mobile infrastructure and a range of mobile devices, with a focus on mobile phones, and the Android platform in particular. Students learn the principles of interactive graphical user interfaces for mobile devices and look at the protocols and standards for using mobile device features such as sensors, networking, location, camera, and audio. They also discuss mobile app architecture, performance considerations, and asynchronous programming--along with the principles and technologies for mobile security. Prerequisite: CS 5044.
Basic principles and techniques for big data analytics, including methods for storing, searching, retrieving, and processing large datasets; introduction to basic machine learning libraries for analyzing large datasets; data visualization; case studies with real-world datasets. Prerequisite: CS 5044.
Social media platforms, media feeds, and data formats; machine learning and graph theory foundations for social media analytics. Forms of social media analytics - text analytics, network analytics, and action analytics. Forecasting models and applications, including in marketing, event tracking, surveying and A/B testing. Prerequisite: CS 5044.
This course focuses on critical aspects of the software lifecycle that have significant influence on the overall quality of the software system including techniques and approaches to software design, quantitative measurement and assessment of the system during implementation, testing, and maintenance, and the role of verification and validation in assuring software quality. Prerequisite: CS 5044 AND CS 5704.
Cybersecurity principles and technologies motivated by the evolving ecosystem of the Internet of Things (IoT): devices, operating systems, sensors, data storage, networking and communication protocols, and system services. IoT device and system security and privacy vulnerabilities, analysis and attack mitigation techniques. Prerequisite: ECE 5484 OR CS 5044.
Fundamental principles and concepts of computer networks, application, transport, network, and data link protocols. Contemporary and emerging networks; Internet protocols. Principles of quality of service, network security and network management. Prerequisite: ECE 5484.
The convergence of digital technologies in networked devices, big data, and advanced break-throughs in artificial intelligence (AI) and machine learning (ML). The meaning, theory, and construction of socio-technical systems. Analysis of the technical aspects and opportunities of AI/ML systems in emerging organizations. Technosystem due diligence of advanced AI/ML systems, and assessment of the viability of emerging technological solutions and the social impacts of disruptive change upon individuals, organizations, and society-at-large. Frameworks for the design and implementation of advanced AI/ML systems, and planning for the future of this technology. Prerequisite: ECE 5484 OR MGT 5804.
Fundamental Internet and computer security principles and applications; legal and privacy issues; risk analysis, attack techniques, intrusion detection concepts, basic computer forensics, and system and application security hardening techniques. Prerequisite: ECE 5484 required; CS 5044 recommended.
Advanced security and trust concepts and implementation in wired and wireless computer networks; computer systems malware defenses; impacts of channel fragility, node mobility, and cooperative functionality, and resource constraints on security and trust at the different layers of the Internet protocol stack. Prerequiste: ECE 5484 AND ECE 5585 required; CS 5044 recommended.
Fundamentals of data engineering. The role of a data engineer. Data engineering lifecycle. Data quality and valuation. Data provenance. Data generation, ingestion, transformation, storage, serving Artificial Intelligence and Machine Learning (AI/ML), visualization, and business analytics. Automation and task orchestration. Data systems. E(xtract)T(ransform)L(oad) data. Build, test, and maintain data pipelines. Data lakes. Real-world problems with an emphasis on end-to-end engineering solutions. Cloud services and open-source data engines/platforms. Engineering portfolio.
Basic concepts in mobile networks: radio access environment, metrics, core network architecture. NextG use cases, user scenarios, minimal requirements, and Key Performance Indicators (KPIs). Cloud-based mobile networking. Technology enablers for NextG: millimeter wave, terahertz communications, cell-free massive MIMO, intelligent reflecting surfaces, Network Function Virtualization (NFV), Software Defined Networking (SDN), Open Radio Access Network (O-RAN), network slicing, machine learning for wireless, digital twins, edge computing. Security, trust, and privacy in NextG. Business and policy aspects of NextG. Prerequisite: ECE 5484 or CS 5044.
Quantum information technologies for students from diverse educational and professional backgrounds. Principles of quantum mechanics. Qubits, quantum logic gates and quantum circuits. Quantum entanglement as a key resource for information processing. Various physical implementations of qubits. Important quantum computation algorithms and communication protocols. Basic quantum programming skills based on Qiskit and IBM Quantum Lab. Critical review and evaluation of cutting-edge ideas, proposals, advances and debates in public and private sector quantum enterprise. Prerequisite: ECE 5484.
This course delves into the complexities of sociotechnical systems and explores unintended consequences. It examines the relationship between the engineering profession and society, providing frameworks for critical engineering practices. Topics include the dissemination of innovative ideas, risk assessment, precautionary measures, and innovation constraints. Students will study governance mechanisms through case studies of existing technologies like cybersecurity, the Internet, and information technology. The course also covers characteristics and case studies of emerging technologies, along with governance frameworks and assessment tools. It addresses the dynamics of hype and expectations in technology and analyzes governance strategies for specific emerging technologies such as artificial intelligence, nanotechnology, quantum computing, autonomous vehicles, and neurotechnology. Additional discussions encompass technologies serving democracy and public interests, with a focus on future technology governance.
Entrepreneurship in technology-based startups, corporate, and public-sector organizations operating in digital environments. Experiential activities in commercialization and resource mobilization strategies. Design and validation of digital business models for launching technology-based ventures. Assessment and pursuit of entrepreneurial opportunities in cybersecurity, automation, artificial intelligence, and machine learning. Prerequisite: MGT 5804 OR ECE 5484.