Master of Science in Information Technology
Master of Science in Information Technology
The Master of Science in Information Technology (MSIT) curriculum is both innovative and practical, preparing students to skillfully plan, implement and oversee sophisticated IT systems. It is designed to provide students with skills that can be immediately applied to workplace IT systems and to solve real-world information technology problems.
You can choose a speciality track in cybersecurity, data analytics or IT management, or you can pursue a general MSIT degree. Please note that elective courses for the specialty tracks are only available on campus at our Thousand Oaks location.
36 credits total
All courses are 3 credits unless otherwise noted
All MSIT students must complete the eight core courses below for 24 credits total.
In today's dynamic and competitive economy, the ability of an organization to effectively leverage their existing and emerging information technologies is a critical success factor in gaining and sustaining a strategic advantage.
This course introduces students to important concepts and techniques needed to understand and leverage information technology within an organizational context. Students will learn the fundamentals of design and implementation of information systems in the modern organization, business process improvement through the use of information technology, organizational data modeling, project management concepts, data governance mechanisms, technology-enabled change management, among others.
Data is a valuable organizational resource. As organizations collect more and more data, it becomes increasingly important to understand basic principles of how to store and manipulate organizational data in order to successfully run business operations.
This course provides students with an introduction to the fundamental concepts, techniques and tools used in design, development and application of relational database technology in organizations. Topics include data modeling based on organizational requirements and data manipulation via structured query language tools.
This course uses structured software development methodologies to develop an understanding of the overall process of developing an information system starting with planning, analysis, design and implementation of the system. It focuses on the core set of skills that all system analysts must possess, from gathering requirements and modeling business needs, to creating blueprints for how the system should be built and assessing usability.
The course also exposes students to various graphic modeling processes such as data flow diagrams used in business process reengineering, design of user interfaces and system behaviors.
This course is an introduction to the basic fundamentals of project management based on the Project Management Institute (PMI) body of knowledge. All phases of the project management cycle are covered including project initiating, planning, executing, monitoring and controlling project status and post project lessons learned analysis.
In addition, the course introduces the ten project management knowledge areas as defined by PMI: project integration, scope, time, cost, quality, human resources, communications, stakeholder, risk and procurement management. Project management best practices, tools and techniques along with constraints and trade-offs in managing projects are discussed. The course has a practical component with students executing projects as part of teams.
Security of informational assets has become a keenly debated issue for organizations. Effective information security management demands a clear understanding of technical as well as socio-organizational aspects.
The purpose of this course is to prepare students to recognize the threats and vulnerabilities present in current information systems and how to plan for such risks. The course covers a broad range of topics including data classification, cryptography, network and application security, risk management, threat and vulnerability analysis, computer forensics and policies and architecture designs. Students will have the opportunity to try real security and attack tools to understand how they work and how they might be used and counteracted.
Data analytics is the process of analyzing raw data using machine learning algorithms and discovering patterns and associations in large data sets. It supports decision making by detecting patterns, devising rules, identifying new decision alternatives and making predictions. This course provides an overview of leading analytics and machine learning methods and their applications to real-world problems. It is designed to provide students with the skills needed to perform analytical tasks such as prediction and classification using both supervised and unsupervised learning techniques. Students will use available software to conduct various data analyses to detect patterns, predict future trends and help businesses make proactive, data-driven decisions. Students will also investigate the applications of a wide range of modern analytics techniques to business contexts.
Students complete four elective courses (12 credits) from one of the specialty tracks listed below. Alternatively, they can complete a general MSIT degree by selecting four elective courses across the options below.
More and more organizations are collecting large amounts of data, much of it unstructured. Big Data technologies can be used to store, process and analyze large amounts of data using a distributed environment. This course introduces students to the world of big data and associated technologies. The focus of the course is Apache Hadoop, which is an open-source software project that enables distributed processing of large data sets across clusters of commodity servers. The objective of this course is to provide students a foundation for understanding big data technologies and Hadoop in particular.
Topics include Hadoop system architecture, Hadoop Distributed File System (HDFS), MapReduce programming model and design patterns and technologies surrounding Hadoop ecosystem such as Pig, Hive and Oozie. The course will also introduce big data science concepts and NoSQL database technologies.
Ethical hacking or penetration testing is the act of breaking into a system with the permission and legal consent of the organization or individual who owns and operates the system, with the purpose of identifying vulnerabilities to strengthen the organization's security.
This course introduces students to the principles and techniques of the cybersecurity practice known as penetration testing and covers various tools and methods commonly used to compromise and control access to information systems. As part of this course, students will conduct hands-on penetration tests in a controlled lab environment, discover how system vulnerabilities can be exploited and learn how to avoid such problems in order to better secure organizational data and systems.
Students with backgrounds outside of IT or business may need to complete foundation courses, which do not count toward the 36 credits required for the degree.
Organizations are becoming more dependent on sophisticated information systems, mobile technologies, the Internet of Things, machine learning and cloud computing. These technologies and systems do a great deal to improve our lives, however, they are not invulnerable to cybersecurity attacks.
Students who choose this track will become experts in the identification and assessment of information security risks, and they will learn to develop and implement solutions to protect organizational systems from cyber threats through offensive and defensive planning and incident response. They can go on to become cybersecurity analysts, threat analysts, cybersecurity auditors, risk managers, cyberforensics analysts and more.
Learn how to create, develop and implement data models and gain experience working with big datasets using a real-world data cluster to derive insights and make recommendations. The curriculum is rooted in machine learning, statistical techniques, visualization tools and R language.
Students who complete this track will be prepared to leverage and manage data and develop data-driven solutions, either as in-house experts and managers or as independent consultants. This track provides a foundation for graduates to become business/systems analysts, data analysts, business intelligence analysts and the increasingly diverse positions field.
Students who complete this track will be prepared to create strategies that support business, innovate with IT and manage projects, as well as develop and maintain IT architecture and infrastructure.
This specialization is designed to meet the needs of professionals looking to become IT managers, IT Project managers, IT consultants, IT strategists, chief information officers (CIO) or chief technology officers (CTO), among other positions.
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