Academics

The Smith School's MS in Information Systems is designed for full-time students. The 30 credit program can be completed in as little as nine months, though most students complete the program in 16 months. International students who require student (F-1) visas should plan on completing the program in no more than 16 months.

Required Courses

Elective Courses

Curriculum

1st Semester

Data Models and Decisions (3) 

Database Management Systems (3) 

Data Processing and Analysis in Python (3) 

Strategic and Transformational IT (2) 

Managing Digital Business Markets (2) 

2nd Semester

Business Process Analysis (3) 

Project Management (2)

Choose Two:

Data Mining & Predictive Analysis (3)

Computer Simulation for Business Applications (3)

Google Online Analytics Challenge (3)

3rd Semester

Choose Two:

Applied Finance Information Systems (3)

Big Data and Artificial Intelligence for Business (3)

Decision Analytics (3)

Healthcare Information Systems (3)

Management of Information Systems (3)

Required Courses

BUSI758B: Data Models and Decisions

Credits: 3

Explores basic analytical principles that can guide a manager in making complex decisions. A good decision uses sound reasoning and takes into account all of the relevant information that is available at the time the decision is to be made. In order to arrive at a good decision, a manager must be able to:

  • Identify an underlying analytical structure in a seemingly complex and amorphous decision problem
  • Understand the role of uncertainty and risk in the decision-making process
  • Analyze available data to understand relationships among variables and to create predictions
  • Understand the trade-offs involved in the decision
  • Use available computing technology (e.g., spreadsheets) to arrive at optimal solutions.

BUDT758X: Data Processing and Analysis in Python
Credits: 3

This course provides an introduction to the Python programming language for the purpose of processing, analyzing, and visualizing data. In addition, students will be introduced to developing basic regression, optimization, and simulation models in Python, using highly popular packages. Course emphasis is on mastering basic Python functionality and developing intermediate to advanced skills in working with data, through instruction and active learning. 

BUDT758Y: Database Management Systems
Credits: 3

Introduction to the conceptual and logical design of relational database systems and their use in business environments. Topics include information modeling and optimization via normalization; Structured Query Language (SQL); Client/Server architectures; Concurrency & Recovery; Data Warehousing.

BUSI621: Strategic and Transformational IT
Credits: 2

Introduces students to the key issues in managing information technology (IT) and provides an overview of how major IT applications in today's firms support strategic, operational, and tactical decisions. Topics include: synchronizing IT and business strategy; the transformational impacts of IT; evaluating and coping with new technologies; governing, managing, and organizing the IT function including outsourcing/offshoring considerations; assessing the business value of IT and justifying IT projects; and managing IT applications in functional areas to support strategy and business process.

BUSI622: Managing Digital Business Markets
Credits: 2

The objective is to understand the strategic and tactical issues involved in managing digital businesses and markets. Also, some of the characteristics of digital businesses and markets that make them unique and understand how companies can best manage them will be examined.

Business Process Analysis
Credits: 3

Helps students gain a solid foundation in the concepts, processes, tools, and techniques needed in analyzing business processes and conducting information systems projects.

Project Management
Credits: 2

Designed to provide students an opportunity to engage in intensive interaction with senior supply chain executives from a cross-section of industries. Executives share their insights on leading competitive supply chains in the global marketplace, while students research the competitive supply chain dynamics of each executive's industry.

Electives 

BUDT732: Decision Analytics
Credits: 3

Analytical modeling for managerial decisions using a spreadsheet environment. Includes linear and nonlinear optimization models, decision making under uncertainty and simulation models.

BUDT733: Data Mining & Predictive Analytics
Credits: 3

Data mining techniques and their use in business decision making. A hands-on course that provides an understanding of the key methods of data visualization, exploration, classification, prediction, time series forecasting, and clustering.

BUDT758B: Big Data and Artificial Intelligence For Business
Credits: 3

Big data represents unprecedented opportunities for companies to generate insights and create wealth. A huge amount of data is being generated. At the same time, much of the big data is unstructured, in real time and only loosely connected. It defies the traditional ways of managing databases. This creates challenges even to tech-savvy companies on how to leverage the big data to gain competitive advantages. Challenges and opportunities coexist. To extract the great value from the data, we should be equipped with advanced techniques. Artificial Intelligence (AI) is penetrating our daily routines deeply and shows great promise in exciting areas such as healthcare and autonomous driving cars.

This course uses a hands-on, learning-by-doing approach to understanding the concepts behind Big Data and AI, the strategic drivers of these technologies and the value propositions that they provide to industries. In addition, the course will also serve as an introduction to some of the key technologies within this ecosystem, such as Hadoop, AWS, Pig, Hive, Amazon Web Services and Spark. Examples of AI using Deep Learning will be conducted in class. The focus is on creating awareness of the technologies, allowing some level of familiarity with them through hands-on exercises and projects, and enabling strategic thinking around the use of these technologies in business.

BUDT758F: Google Online Analytics Challenge
Credits: 3

BUDT758J: Management of Information Systems
Credits: 3

To work together effectively for an organizations success, both business managers and IS managers must understand how to both manage and utilize information systems. This course explores management issues and opportunities of the IS function within organizations. Topics include e-business, protection of intellectual property and personal information, software development, IS operations, systems availability and business continuity, IS for multinational organizations, shadow IS organizations, business partnerships and alliances, and mergers, acquisitions, and divestitures.

BUDT758M: Healthcare Information Systems
Credits: 3

Health care is the last major industry in the United States to successfully use automation to improve its effectiveness. This course considers the business implications of healthcare information systems. Topics include e-health and operational information systems, electronic medical / health records, EM/HR exchanges, electronic prescribing systems, electronic imaging, testing, and diagnostic systems, systems for preventive care and patient care in hospitals, care facilities, and homes, health care operations, and information privacy, security, reliability.

BUDT758Z: Data Networks and Infrastructure
Credits: 3

Applied Finance Information Systems
Credits: 3

Computer Simulation for Business Applications
Credits: 3

This course covers the basic techniques for computer simulation modeling and analysis of discrete-event systems. Course emphasis is on conceptualizing abstract models of real-world systems (for example, inventory or queuing systems), implementing simulations in special purpose software, planning simulation studies, and analyzing simulation output.

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