Online Master's Degree in Artificial Intelligence

This course explores how organizations use AI for business transformation and strategic decision-making through real-world case studies. Students examine AI adoption frameworks, leadership strategies, and ethical deployment across industries. Topics include AI scaling, automation, competitive differentiation, and ROI, with case studies preparing students to lead technological change.

An in-depth investigation of the theories, methods, and techniques of various machine learning models. Topics include how artificial intelligence differs from programming; supervised and unsupervised learning models and techniques; validation strategies; data preparation and imputation; organizational, ethical and leadership applications and challenges.

This course is an introduction to the use of Business Analytics and big data as a strategic resource. A focus is placed on integrating the knowledge of analytics tools with an understanding of how companies leverage data analytics to gain strategic advantage. The key areas of customer analytics and surveys of data mining techniques and applications will also be covered. Case approach is used to emphasize hands-on learning and a real-world view of Business and big data analytics.

This course explores AI-powered automation in business, covering chatbots, workflow optimization, and decision support. Students apply low-code AI tools, prompting, and automation strategies to enhance efficiency. Ethical and security implications are examined, preparing students to implement AI-driven solutions in evolving business environments.

Using large-data analytics tools to develop visual representation of high-dimensionality data to communicate results, predictive, and prescriptive data to management and decision makers. Theory of various visualization techniques, identifying and correcting misleading visuals, documenting and communicating results. MS PowerBI will be used a platform for exercises.

This course will enable the student to understand the current state to the IS Consulting profession and follow its development, articulate the pros and cons of various IS consulting initiatives, and develop a plan to join or start a consulting firm.

The course will also cover benchmarking, quantitative analysis and the voice of the customer. The design of the course involves case discussion, lectures, and problem solving as the primary vehicle for learning. In addition, a project is due at the end of the term, to give the class a laboratory in which the critical thinking skills, which will be sharpened in the class, can be used in initialize and analyze various projects. Investigates the project management methods, tools, and techniques used to analyze and develop organizational information systems.

This course introduces students to artificial intelligence in investment management. Students apply tools such as natural language processing, forecasting, and workflow automation to analyze financial data, evaluate corporate performance, and manage a real-money portfolio, with emphasis on ethical evaluation and strategic decision-making in asset management and fintech.

Hardware required for effective machine intelligence in research and production environments, GPUS, the Linux OS, Python, structured data, unstructured data, and blockchain methodologies as applied to machine intelligence. Includes use of computer lab for exercises in various techniques to leverage off-the-shelf and cloud-based technologies for maximizing investment.

Theoretical examination of neural networks at the structural level and topological impacts of hyperparameters on deep learning models. An in-depth review of the methods and techniques of various deep learning models as applied to common and novel data sets. Topics include model selection for maximizing performance, theories for generalizing, bias reduction, ethical challenges, and future directions of the field.

This course will enable the student to use innovation as a competitive situation for organizations, to analyze and critique innovation approaches, create a significant strategic technology policy, and to build a portfolio management office in the government agency or organization.

This course provides students an understanding of technologies and methodologies used to manage information technology and/or information systems projects. Terminology will be discussed along with techniques to accurately gauge and manage project complexity, risk, scope, time, and resources. Covers project management concepts and documentation. Students will learn how to manage projects, including working with and using Microsoft Project in teams.

Exploration and development of emerging AI technologies and a small team project identifying a problem for an external client organization, or a specific internal research project, to plan, execute, and complete an application of AI to address the problem or research question. Students will deliver the completed algorithm and supporting documentation to the client or researcher.