Curriculum

Core Courses (18 credits)

• Project Management

  This course examines the defining characteristics of IT projects and introduces a variety of relevant techniques. The course includes project manager functions like managing scope, time, quality, and cost.  Students will learn about project management methodologies such as the AGILE method.

  Software: Microsoft Project 2016

• Database Management

  This course will help students critically think about how to conceptualize and model databases, and use query languages to manipulate databases to obtain information that can help a manager make decisions. The course takes a transaction-based (OLTP), data-oriented view that is embedded in the larger processing view. The course is primarily driven by problem-solving exercises and case discussions in a collaborative environment. Students should be able to extend their learning to unfamiliar environments and applications, and to communicate their knowledge.

  Software: SQL, Visio, Lucidchart, Access, Neo4j, Tera

• Business Process Design

  This course focuses on the fundamental concepts, frameworks and techniques that can be used to analyze and redesign business processes through strategic and operational mappings and alignment between strategy, process and technology. The course covers how to map strategy, process and technology and how to conduct business process as-is and to-be, analysis and design.

  Software: Microsoft Visio, LucidChart, IBM Process Integration Modeler

• Systems Analysis and Design

  This course will introduce students to the field of Systems Analysis and Design in general, and focus in depth on object-oriented concepts, methodologies, models and skills, along with associated software tools. In this course, we will consider the case where custom software is required to solve a business problem or automate a business process. To this end, we will consider the major object oriented methodologies, and follow a lightweight version of the Rational Unified Process in case study form. All of these methodologies require a consistent means of describing various dimensions of a software design. The Unified Modeling Language (UML) provides an industry-accepted standard graphical language for describing different aspects of a software system. We will cover some of the major parts of the UML in this class.

  Software: Unified Modeling Language (UML)

• Information Security Management

  This course focuses on the managerial aspects of information security. Topics covered include access control models, information security governance, and information security program assessment and metrics. Coverage on the foundational and technical components of information security is included to reinforce key concepts.

  Software: Wireshark, Webgoat, Security Onion

• Information Systems Strategy and Governance

  The focus of this course includes: 1) The top management's strategic perspective for aligning competitive strategy, core competencies, and information systems (IS); 2) The development and implementation of IS strategic plans to achieve organizational goals; 3)  Frameworks for creating IS value; and 4) Methodologies for designing the IS organization in accordance with IS governance best practices.

  Students develop an understanding of the strategic use of IS from a business perspective at the enterprise level. They are expected to understand the competitive environment from the point of view of the CIO and to examine strategies and tactics available to use information systems for competitive advantage. Students will also understand how to define and implement IS governance to enable both business and IS executives to execute their responsibilities, in support of business/IS alignment and value creation.

Business Analytics Track
16 months, starts in fall (August)

Provides advanced analytical skills and knowledge in big data and quantitative analysis. You will gain a unique combination of analytical and information systems management skills utilized to uncover trends and predict patterns specific to businesses. You will develop the skills and know-how to provide critical insights and recommend solutions on how businesses can increase their effectiveness through their processes, products, services, software, and technology systems.

Specialized Courses (18 Credits)

• Python Fundamentals for Business Analytics

  This course will provide an understanding of fundamental python concepts and libraries needed in data science and business analytics.

  Software: Python

• Quantitative Analytical Methods in Business

  This course provides a review of the quantitative analytical techniques required for statistical and business analysis and decision making using programming languages such as Python. Students will learn about the use of quantitative methods for turning data into information and information into good business decisions for managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, this course introduces students to the important role that data plays in understanding business outcomes and improving business processes.

  Prerequisite: Python Fundamentals for Business Analytics

• Machine Learning for Business Applications

  This course focuses on the use of machine learning approaches to analyze data effectively and extract useful information from a large amount of data to support business decision making.

  Software: Excel, Rapidminer, R, Python

  Prerequisite: Python Fundamentals for Business Analytics

• Business Data Visualization and Exploration

  This course covers business data exploration and visualization techniques, with structured and unstructured data. Topics include overview of data visualization, understanding dimensions and measures, data wrangling and blending, formulating practical research questions, matching questions with basic/advanced chart types, calculation and parameter, creating dashboards and stories, and dashboard critics.

  Software: as Tableau, Python, R

  Prerequisite: Python Fundamentals for Business Analytics

• Data Warehousing

  In this course, students will design and implement an enterprise data warehouse architecture, utilize ETL tools and techniques to load data into the data warehouse, build and deploy multi-dimensional cubes, and utilize powerful reporting tools to analyze large volumes of data and convert these data to useful information. Using powerful data visualization tools, students will learn how to use data to explain the past, monitor the present, and anticipate the future.

  Software: SQL Server RDBMS, SQL Server Analysis Services, SQL Server Data Tools, Tableau reporting software, Power BI, Python scripting

• Business Analytics Capstone (project-based)

  This capstone course synthesizes and applies the knowledge learned on managing business analytics across courses in the business analytics track.

Artificial Intelligence Track
12 months, starts in spring (January)

Provides a deep understanding of how to leverage AI to effect digital transformation, value creation, and competitive advantage. Students will focus on developing AI skills and the ethical implementation of AI in business. Courses will cover AI technologies, their development, and business applications and strategies. With a strong emphasis on ethical considerations in AI, graduates are prepared to develop, evaluate, refine, and implement AI-related applications and technologies responsibly in various industries, and pursue careers in information systems in both private and public sectors.

Specialized Courses (18 Credits)

• Python Fundamentals for Business Applications

  This course will provide an understanding of fundamental python concepts and libraries needed in data science and business analytics.

  Software: Python

• Quantitative Analytical Methods for Business

  This course provides a review of the quantitative analytical techniques required for statistical and business analysis and decision making using programming languages such as Python. Students will learn about the use of quantitative methods for turning data into information and information into good business decisions for managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, this course introduces students to the important role that data plays in understanding business outcomes and improving business processes.

  Prerequisite: Python Fundamentals for Business Analytics

• Machine Learning for Business Applications

  This course focuses on the use of machine learning approaches to analyze data effectively and extract useful information from a large amount of data to support business decision making.

  Software: Excel, Rapidminer, R, Python

  Prerequisite: Python Fundamentals for Business Analytics

• Artificial Intelligence Strategy

  This course uses artificial intelligence methods to analyze and extract useful information from unstructured data to provide real-time knowledge to incorporate artificial intelligence into the business strategy.

• Business AI Applications

  This course provides an in-depth understanding of how Al is applied in business. It covers a range of methods, their implementation, and their use in solving business problems.

• Business AI Capstone (project–based)

  In today's digital landscape, virtually all organizations heavily depend on information systems. Efficient utilization of these systems requires navigating complex management challenges using Al. This capstone course synthesizes and applies the knowledge learned on managing artificial intelligence across courses in the artificial intelligence track.