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Semester Two
This course teaches the technical and managerial skills needed in developing predictive analytics applications which are used by customer-centric corporations - retail, financial, communication, and marketing groups - to help make decisions involving complex systems. The course concentrates on a set of well-known predictive analytics methods to support business decision making. Topics such as association rule mining, decision trees, neural networks, regression analysis and cluster analysis are covered in great depth. Extensive hands-on experience using software such as SAS Enterprise Miner is provided.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
The focus of this course will be on technology management and developing an Internet-based business or extension to an existing business. The course will integrate concepts from economics, organizational strategy, entrepreneur-ship, and Web design. Topics to be covered in the course include: aligning technology and strategy; models of diffusion and innovation; characteristics of information and digital goods; identifying potential Web-applications and information products for solving a problem and/or identifying a business opportunity; intellectual property rights; pricing issues related to information goods; developing a business plan for a venture capital proposal; launching the e-business; designing Web based applications for usability; and strategies for successfully implementing systems. Case studies, lectures, guest speakers, and an integrated E-business project will be used to understand the complexities of the current business environment.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
At least 3 credits from:
This course provides an exposure to Information Systems used in the delivery of healthcare. Specifically this course will introduce students to IT systems that are deployed at a variety of organizations such as Hospitals, Ambulatory Care, Home Health, Tele Health and Online communities to better understand how information is gathered, analyzed and disseminated. The course will include content relating to IS Effectiveness and Success, task-technology fit, IT Communications and Compliance, IT Risk modeling and assessment, business modeling of innovations in healthcare services and delivery, and business performance issues relating to the deployment of IT. The course focuses on how current and emerging technologies can be better utilized to improve access, quality of care and business efficiency.
Credits: 3
Semesters offered:
Large scale computing environments aggregate resources from many autonomous computers to satisfy the information processing needs of modern enterprises. This course introduces techniques for creating functional, usable, high-performance distributed systems. Objectives are twofold: (1) gain a solid understanding of the technical issues, concepts and systems in the rapidly advancing technologies in distributed computing, and (2) acquire substantial knowledge on how to work with big data in distributed environments. The course is organized into two parts: study of DCS technologies, and study of large scale systems. We will discuss communication and networking services, application support services, large scale distributed system design, data management and interoperability of systems including consistency and data replication. Students will learn to use a framework for data intensive distributed applications (Apache Hadoop) and an associated parallel programming model, MapReduce.
Credits: 3
Semesters offered: Fall 2023
In large organizations, data invariably resides in multiple-platforms and in multiple formats. Therefore, it becomes essential to pre-process the data at appropriate levels of normalization for meaningful analysis. Extraction, transformation and loading data into structures such as data marts and data warehouses are essential steps to predictive data modeling and mining. These analytical tasks begin with a basic understanding of where the data is stored and how it can be assembled for business purposes. This course provides students with a hands-on introduction to data warehouse design, data cleansing, exploration, and visualization within a cloud-centric ecosystem.
Credits: 3
Semesters offered: Fall 2023
Pre-Requisite or Co-Requisite: MGS 613 (Database M
"This course is broken into two segments. In the first segment we¿ll learn about IPOs, an introduction to the trading process and how it works, and complete the Bloomberg Market Concepts Certification which will cover Economic Indicators, Currencies, Fixed Income, Equities along with introductions to Cryptocurrencies and Bitcoin. Students will be introduced to the early leaders in algorithmic trading and document their own trading strategies. In the second segment of the course, students will gain a solid understanding of order types, ECNs, and the different types of participants in our markets. We will cover topics such as the impact of High Frequency Trading and the usage of Dark Pools."
Credits: 3
Semesters offered:
Pre-Requisite: MGF 611 or MGF 631 (or equivalent)
Capstone (1.5 credits)
A foundational course, which serves as an introduction to the principles and techniques of data visualization. Visualizations are graphic representation of data that can enhance comprehension, communication and decision making for managers. In the course students will learn visual representation methods and techniques. Students will be introduced to the science of selecting the right kind of visualization for a certain type of data. The course will further enable students to communicate information through visual representation in a clear, effective and efficient manner. There is a significant hands-on component in the course and the students will be expected to work on data visualization tools like SAS Visual Analyst, IBM Watson, Tableau, etc. as part of the recitation.
Credits: 1.5
Semesters offered: Spring 2024
* MGS 626 is 1.5 credits in this program.
Total credits: 12
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The focus of this course will be on technology management and developing an Internet-based business or extension to an existing business. The course will integrate concepts from economics, organizational strategy, entrepreneur-ship, and Web design. Topics to be covered in the course include: aligning technology and strategy; models of diffusion and innovation; characteristics of information and digital goods; identifying potential Web-applications and information products for solving a problem and/or identifying a business opportunity; intellectual property rights; pricing issues related to information goods; developing a business plan for a venture capital proposal; launching the e-business; designing Web based applications for usability; and strategies for successfully implementing systems. Case studies, lectures, guest speakers, and an integrated E-business project will be used to understand the complexities of the current business environment.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
This course is designed to provide students with a basic understanding of database management systems (DBMS) and the skills needed to design and implement a relational database. Students will be introduced to data modeling concepts, modeling tools, the process of transforming conceptual models into relational database designs, and finally the steps needed to implement those designs. Emphasis is placed on Entity-Relationship diagramming, data normalization, database administration, and data definition, data manipulation and query development using Structured Query Language (SQL). Other topics covered include: object-oriented databases, database security and integrity, web/database integration, application development in a Client/Server environment, distributed databases, data warehousing, data mining and knowledge management via the Internet to support electronic commerce. Readings, lectures, interactive case assignments and a database design project reinforce the role of DBMS in supporting organizational systems, transaction processing and decision support applications.
Credits: 3
Semesters offered: Fall 2023
This course covers the fundamental concepts in statistics that are essential for business and data analytics. Probability Theory and Sampling Theory are the two foundations of both descriptive and predictive forms of analytics. Building from these foundations, students are introduced to the statistical concepts of data analysis. Topics covered include: descriptive statistics, probability theory, discrete and continuous probability distributions, sampling theory, estimation, hypothesis testing, distribution fitting using chi-square tests, simple and multiple linear regression, introduction to causal modeling and predictive data analytics. MS-Excel based data modeling will be used extensively throughout the exposition of the concepts.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
*MGQ 606 is only required for students without a business background.
• Three electives (3 credits each)
*Students without a business background are required to take MGG 503 and MGQ 606; students with a business background may be waived from these courses.
MGS 613 is a component of the Information Assurance certificate. If you take three of these elective courses, you will be eligible for the certificate in addition to the MS degree. See additional information on the Information Assurance certificate.