Master of Science in Information Systems Curriculum
Fall 2019/Spring 2020
Maryland Smith’s curriculum is interactive, data-focused and adjusts to reflect the trends of the modern business world. The courses you’ll take are taught by knowledgeable scholars and experts with years of experience leading others in their field.
Managing Digital Business Markets
2 credits | BUDT 758G
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.
Data, Models, and Decisions
3 credits | BUDT 758Q
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.
Database Management Systems
3 credits | BUDT 758Y
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.
Data Processing and Analysis in Python
3 credits | BUDT 758X
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.
Strategic and Transformational IT
2 credits | BUDT 758E
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.
Project Management for Dynamic Environments
2 credits | BUDT 758C
Addresses project management skills that are required by successful managers in increasingly competitive and faster-moving environments. Examines fundamental concepts of successful project management, and the technical and managerial issues, methods, and techniques.
Business Process Analysis for Information Systems
3 credits | BUDT 758N
Helps students gain a solid foundation in the concepts, processes, tools, and techniques needed in analyzing business processes and conducting information systems projects.
Computer Simulation for Business Applications
3 credits | BUDT 758K
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.
Google Online Challenge Analytics
3 credits | BUDT 758F
Data Mining and Predictive Analytics
3 credits | BUDT 758T
In business magazines, on TV, and in board rooms, “big data” and “data analytics” are now hot topics. Vast quantities of data are being generated these days, including new types of data such as web traffic, social network data, and reviews and comments on websites. This data is a valuable resource that, when used correctly, can create a competitive edge for companies by improving the quality of decision making. Recent advances in computing hardware and software have made the application of advanced analytical methods much easier.
This course takes advantage of these developments to introduce data analytics to those interested in developing expertise in data-driven decision making. The course is intended to provide an introduction to the tools and techniques of data mining & machine learning that are central to business analytics, with particular emphasis on classification and prediction. The focus will be on business applications and examples from Marketing, Finance, Healthcare, and Operations will be used to illustrate the breadth of applications.
Big Data and Artificial Intelligence for Business
3 credits | BUDT 758B
Big data represents unprecedented opportunities for companies to generate insights and create wealth. 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.
3 credits | BUDT 758I
The focus of the course is to provide relevant background in financial industry and leverage student’s IT background to position them for possible IT/IS opportunities in financial industry. Topics covered will include R and Python for finance, credit risk management, portfolio analysis, financial trading, and time series data analysis.
This course will help students get various job position in ever-expanding financial industry. It provides a bridge between Financial domain and Information Systems. Some job positions that students may look after taking this course are Business Consultants, Financial Consultant, Financial Analysts, Credit Analyst, Credit Risk Managers, Portfolio Manager, Wealth Management Analyst and lots of other jobs in Financial Sector.
This course will focus on giving the theoretical foundation of topic covered in the syllabus along with their practical implementation. The course is split in 30:70 ratio of theory to practical. The course will be built upon various practices followed by several Fortune-500 companies. This course will also be accompanied by a major project where students will be practicing the concepts learned in the classes.
Health Information Systems
3 credits | BUDT 758M
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.
Management of Information Systems
3 credits | BUDT 758J
To work together effectively for an organization's 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.
3 credits | BUDT 758P
What makes a decision difficult? Usually, the answer is that the decision requires us to spend scarce resources. A “resource” is any asset that can be leveraged to achieve business objectives: time, money, staff, trucks, computer cores, and research effort can all be viewed as resources. When you decide to spend your resource on something (e.g., investing into a research project, or accepting a delivery job), there is less of the resource that can be spent on something else. You thus have to think carefully about the tradeoffs involved in allocating resources to one objective as opposed to another.
This class develops a quantitative framework for studying resource allocation problems. Resource allocation problems arise in many industries and areas such as transportation, electronics, advertising, finance, and health care. The specifics of each problem are very different. Nonetheless, all resource allocation problems, in all of these areas, have common elements that behave in exactly the same way. We will develop an abstract modeling language that emphasizes these common elements, so that you will be able to write down any resource allocation problem on paper and then apply standard tools (such as Microsoft Excel) to obtain solutions.