The Master of Professional Studies in Game, Entertainment, and Media Analytics (GEM) degree requires you to complete 30 credit hours of academic work with at least a B average (3.0 GPA). This includes ten (10) three-credit courses. Full-time students complete the program in one year. Part-time students can take up to five years to complete the program.
|Fall||Winter||Spring||Summer (Full Summer)||Summer I||Summer II|
|INST-737: Introduction to Data Science||INFM-605: Users & Use Context||INST-728E: Game Design||INST-731: Advanced Game, Entertainment, and Media Analytics||INST-751: IoT/Streaming Analytics||INST-760: Data Visualization|
|INST-661: Introduction to Game, Entertainment, and Media Analytics||INST-767: Big Data Infrastructure|
|INST-730: Entertainment Environments||INST-756: Information Risk Management|
INST-737: Introduction to Data Science (3 credits)
An exploration of some of the best and most general approaches to get the most information out of data through clustering, classification, and regression techniques.
INST-661: Introduction to Game, Entertainment, and Media Analytics (3 credits)
With the continuing global growth in the Game, Entertainment, and virtual/augmented reality and immersive experiences industries, entertainment providers increasingly depend on data analytics to maintain a competitive edge while continuing to improve the customer experience. This course provides an overview of the Game, Entertainment, and Media (GEM) industries, discuss the relationships between the entertainment providers and the entertainment consumers and explore the analytical techniques used to maximize the overall value to both the providers and consumers. The course will focus on the uses of analytics methods such as personalization, recommendation, clustering and segmentation, behavioral analytics, etc., will discuss core data management and data architecture concerns, and examine how big data infrastructure can support scalability as data volumes grow and as streaming speeds accelerate. In addition we review socio-technical aspects of entertainment, especially in the areas of cyberpsychology, social networks, and information policy concerns such as privacy protection, fraud, equity, and national security concerns.
INST-730: Entertainment Environments (3 credits)
Use of information by individuals. Nature of information. Information behavior and mental models. Characteristics of problems, task analysis, problem solving, and decision making. Methods for determining information behavior and user needs. Information access. Information technology as a tool in information use.
INST-728E: Game Design (3 credits)
Games are a structured form of play that is typically undertaken for recreational—but sometimes also educational and even professional—purposes. There is evidence of games dating back thousands of years, indicating that they are central to the human condition. But what constitutes a successful game? In this course, you will learn the fundamentals of game design: applying elements and principles of game design, such as goals, rules, and challenges to create games, such as board games, card games, and digital games. You will be introduced to the basic tools and methods of game design: paper and digital prototyping, design iteration, design critique, and user testing. As part of the course, you will be designing several games of different types, each which you will be able to add to your growing portfolio of game design concepts. You will also learn how to use your skills to deconstruct and critique the components of existing games, as well as gain an understanding of the role of the game designer in real-world game development teams.
INST-767: Big Data Infrastructure (3 credits)
Principles and techniques of data science and business intelligence. Technologies and architectures for large-scale data warehousing and scale-out data analytics platforms. Supervised and unsupervised data mining.
INST-756: Information Risk Management (3 credits)
Over the past two decades, there has been a plethora of government legislation and regulation impacting organizational information management. At the same time, the risks of exposure of protected information have intensified due to a widening array of cyber threats and attacks originating from both outside and within the organization. This course looks at information management from a risk perspective, including an examination of system threats and vulnerabilities. The course will also explore how statutes and regulations provide a framework for defining what is considered to be protected information in varying sectors of the commercial world, as well as in government. The course considers how data assets are assessed and classified in terms of their levels of sensitivity. In addition, the course discusses information governance and data protection policies applicable to mitigating information risk and enforcing compliance within organizations.
INST-731: Advanced Game, Entertainment, and Media Analytics (3 credits)
INST-751: IoT/Streaming Analytics (3 credits)
This course reviews various methods, technologies, and architectures encompassed within the world of IoT (compute platforms, communications, data management, and analytics). We will review the building-block technologies and how they have evolved to support the IoT world’s strengths and simplicity. We will discuss a variety of uses cases where IoT and the associated technologies are implemented in the real world across various industries.
INST-760: Data Visualization (3 credits)
explores the application of data science techniques to unstructured, real-world datasets including social media and geo-referenced sources. The course will focus on techniques and approaches to extract information relevant for experts and non-experts in areas that include smart cities, public health, and disaster management. The course will examine state-of-the-art research in the field and will put an emphasis on mastering current literature and trends. Students will be required to read and present papers in class as well as to participate in technical discussions. The course will also have an important practical component with students working on a variety of research problems through a data lens.
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