Master of Science in Artificial Intelligence Systems

Program Requirements

Required Courses

MAIN 610

AI Principles and Practice

This course explores the fundamentals of Artificial Intelligence (AI), emphasizing ethical considerations and practical applications across diverse sectors. Participants will gain essential AI knowledge, learn to evaluate ethical dilemmas, and enhance their ability to implement AI strategies in real-world scenarios, fostering innovative and ethical problem-solving skills.
3 Credits

MAIN 620

The Practice of Generative AI

Operational aspects of generative artificial intelligence, focusing on the art of prompt engineering, methodologies for effective evaluation of AI implementations, and effective system integration methods.
3 Credits

MAIN 622

AI for Predictive Analytics

This course is designed for students to master the art and science of classifying data and predicting trends. Students will learn statistical methods, data mining,and advanced analytics, using innovative machine learning tools and platforms to forecast outcomes in various domains. The course emphasapplications, including how toeffectively collect, analyze, and interpret data, students develop a keenunderstanding of model assessment and selection to inform strategic decisions.
Prerequisite: Basic Statistics.
3 Credits

MAIN 625

AI System Design

Students learn how to design systems and processes that use AI as a key component. This course emphasizes the design, imple management of AI-driven processes across various applications, including, but autonomous systems, predictive analytics, and intelligent interfaces. explore how to practically use a variety of AI tools and methods in fields such as health customer service, marketing, autonomous vehicles, smart cities, and monitoring, among others, with a focus on real-world applications. Learning is through a case studies and practical exercises.
3 Credits

Elective Courses (Choose 2)

MDAN 631

Fundamentals of Visual Data Analytics

Data visualization is an essential storytelling tool for exploratory and explanatory analysis. This course navigates real-world business problems ac industries, focusing on iteratively deriving solutions through static a dashboards. Students will gain hands-on experience with the latest cloud BI software, and structuring relations between disparate sources. Working in agile-like w students will learn to identify patterns and anomalies, conduct prescriptive analyses, a communicate insights to influence decision making of technical and non-technical stakeholders.
3 Credits

MDAN 642

Digital Marketing Analytics

This course is meant to integrate a virtually frictionless system for moving from data to decision, action to results! The course will explore how to:

• use analysis to craft experiences that prof customers’ needs, expectations, and behaviors
• measure real digital media ROI: sales, leads satisfaction
• track the performance of all paid, earned, and channels
• leverage digital data beyond PR and marketing: planning, product development, and HR
• start optimizing digital content in real time
• implement advanced tools, processes, and accurately measuring influence
• make the most of surveys, focus groups, and of synergies
• focus new marketing investments where they’ll de value
• identify and understand important audiences acro ecosystem

3 Credits

MSIN 627

Multi-Dimensional Analytics and Visualization Technologies

The course introduces the practice of managing data as corporate assets by organizations to gain competitive advantage and meet regulatory demand. The course will also describe the data management emerging profession, and skills required to perform the various data management functions for each role.
Prerequisite: MSIN 615
3 Credits

MSIN 616

Advanced Database Management and Data Analytics

Building on Database Management and Administration, the course explores additional data modeling techniques, concepts of database integrity and transaction management, stored procedures, user-defined functions, database programming, query optimization, performance and tuning, and other advanced SQL topics.
Prerequisite: MSIN 615
3 Credits

MSIN 633

Data Modeling, Analysis, and Visualization

This course combines lectures with hands-on labs to help students understand transaction systems, data warehouses, fact and dimension tables, design custom columns, custom tables and create multi-dimensional data models based on a wide variety of data sources. Dashboards and widgets of varying complexities will be created using hierarchies, expressions, and functions for data analysis, visualization and decision support.
Pre- or Corequisite: MSIN 616
3 Credits

MSIN 637

Principles of Data Analysis

This course is a hands-on introduction to the field of Data Analytics where students will learn the concepts and tools needed throughout the analysis process from formulating the research question to obtaining, cleaning, and collating data to making inferences and publishing results. Students will also learn how to formulate research questions in “data terms” so that it can be analyzed and identify the limitations imposed by the available data. Students will become versed in sorting data, filtering data and creating data totals. They will learn how to use Pivot Tables. They will also master Statistical Functions, Text Functions, Database Functions, Lookup Functions, and Date and Time Functions among others. Students will be introduced to data types, control structures, functions, and debugging tools. They will learn how to acquire data, what it means to clean data by removing inconsistencies and reformat data so that it can be analyzed by statistical tools.
Corequisite: MSIN 616
3 Credits

MSIN 677

Advanced Data Visualization

In this course, students will explore data analytics and visualization. The course will begin by reviewing analytical methods with an emphasis on the art of crafting compelling data stories. Through lectures, demonstrations, and hands-on tutorials, students will learn how to transform datasets into visualizations and dashboards that communicate key findings and that utilize visual design principles. By the course's end, students will be equipped to present insightful, data-driven narratives that enable decision-makers to discern trends and make informed choices.
Prerequisite: MSIN 627
3 Credits

MSIN 678

Business Intelligence Through Data Visualization and Power BI

This course combines lectures with hands-on labs to teach students necessary skills to connect to Various Data sources, Transform Data, Design Data Models, create, manage, and format Charts/Visuals/DashBoards using various data sources e.g. excel files, SQL Server Databases, and MS Access databases etc. of various complexities & Work with Filtering Students will start with connecting to Datasources, transform data, design models and create simple charts and move onto designing more complex Models and charts of various types including analyzing data over time, trends analysis etc. Advanced formatting, DAX expressions and Filtering will be utilized to make charts stand out.
Prerequisite: MSIN 627
3 Credits

Any Other Elective Approved by the Dean

Any Advance AI Elective Course

Advanced AI Elective Courses (Choose 1)

MAIN 623

Image Analysis and Synthesis with AI

In this course, students will explore visual data interpretation and generation through artificial intelligence. The course provides a comprehensive study of techniques in image processing, analysis, computer vision, and synthetic image generation, emphasizing the use of AI-driven tools. Participants will engage with state-of-the-art AI methodologies to perform tasks such as object detection, image and video classification, and the creation of new imagery through generative models. Focused on practical application, the curriculum guides students through the process of implementing these AI techniques for real-world problems, equipping them with the skills to innovate in the evolving landscape of digital image technology.
3 Credits

MAIN 628

Applications of AI

Students explore how to leverage a variety of AI tools and methods in fields such as healthcare, finance, customer service, marketing, autonomous vehicles, smart cities, and environmental monitoring, among others, with a focus on real-world applications. Learning is through a combination of case studies and practical exercises.
3 Credits

MAIN 670

AI and Society

This course explores the intricate relationship between artificial intelligence (AI) and its societal repercussions, understanding AI’s implications by comparison with historical precedent. This includes consideration of the impact of AI on politics, economics, labor markets, and culture, with a focus on ethical consideration.
3 Credits

Core Technology Management Courses

MSIN 605

Strategic Management of Technology

Enterprises in many industries are driven by the need to achieve technological innovation in order to prosper or even survive. This course focuses on the strategic management of technology and innovation in firms of various types. These technology innovations can encompass software, hardware, or other forms of technology and even the very processes needed to design, develop, and manufacture the resultant technological products. Students develop an understanding of technological innovation and the issues and strategies for organizing, managing, diffusing, and protecting innovation. This broadens the horizons of students who have concentrated on technical computing and Information Technology courses and require enrichment in the area of managerial science.
3 Credits

MSIN 609

IT Project Management

This course is an introductory course that provides the fundamental principles of technology project management. In this course, students will learn how to use Project Management Best Practices to bring order to the otherwise chaotic world of information technology projects, by defining a set of guidelines and standards, and then adhering to them. The student will learn to view Project Management as a set of tools that are an integral part of business strategy. In addition, students will receive a unique perspective on the issues surrounding the management of information technology projects in various organizations.This course will provide students with a solid foundation in IT Project Management.
3 Credits

Capstone Courses (Choose 1)

MAIN 695

AI Research Project

This course is designed to provide students with an individualized research experience, including in-depth study and reporting on a specific topic approved by an instructor. The subject matter must be relevant and advanced in the field of Artificial Intelligence, either from a technological perspective or from an applied perspective, depending on the student's area of concentration.
3 Credits

MAIN 696

AI Internship

This course offers students the opportunity to intern in the field of Artificial Intelligence, culminating in the development of a project or paper based on their approved internship experience. The internship must receive prior approval and should allow students to apply their conceptual, technical, and practical AI knowledge within a professional setting. The internship should leverage the skills and insights gained throughout the program. Students are expected to provide regular progress updates during the internship. International students must apply for CPT to be eligible to work during their internship. All internships require prior approval from the Program Chair. Upon completing the internship, students will be required to pass a recognized certification exam to demonstrate proficiency in an aspect of Artificial Intelligence. Pre- or Corequisite: Approval from the Program Chair.
3 Credits

MSIN 681, 682, 683

Professional Internship Experience 1, 2, 3

These courses provide students with the opportunity to integrate skills presented during course work into real world practice, as well as enhance their awareness of technology in their respective profession. The students will utilize their work as a means of enhancing the educational experience, making on-going strides academically with their professional work. The students will work in a professional environment for a minimum of 240 hours. Students are expected to secure an internship independently. International students are required to apply for CPT for eligibility to work during their internship. Weekly logs and examples of work are required for the successful completion of the internship, and are reviewed by the Faculty Internship Coordinator, upon completion of the internship. The purpose of the internship is to provide students with practical, hands-on experience in their chosen field of expertise to complement their coursework. The Internship MUST be approved in advance by the Program Chair. Students may enroll in MSIN 681 only during the fall or spring semester. MSIN 683 will require students to complete one professional certification at the end of the course to demonstrate their proficiency in their field from the experience acquired throughout the internship and their classes.
1 Credit each

Preparatory Courses

Students with insufficient background in computer science or information systems degree, will be required to complete some or all of these courses:

MSIN 511, MBAN 503, MDAN 609

Introduction to Computers, Statistics and Analytics

This prerequisite consists of three 1 credit modular courses that are all taken asynchronously.

MSIN 511: The IT Essentials (ITE) curriculum emphasizes practical experience to help students develop fundamental computer and career skills. ITE helps students prepare for entry-level career opportunities in ICT and the CompTIA A+ certification. The course also provides a learning pathway to Cisco CCNA.
1 Credit

MBAN 503: This course is structured to enable students to develop and increase their competence in the broad area of statistics and quantitative analysis. Each PowerPoint module will provide definition of terms, the statistics, examples of applied usage & its interpretation. External readings and audiovisual recordings of key concepts will also be required.
1 Credit

MDAN 609: This course will allow the student to comprehend and appreciate creating and working with excel lists. Using multiple worksheets and workbooks. Applying excel editing and web tools. Developing an excel application. Students will use tutorial lab exercises to grasp the above excel concepts.
1 Credit each

MDAN 608

Introduction to Programming (Python)

This course introduces core programming basics—including data types, control structures, algorithm development, and program design with functions—via the Python programming language. The course discusses the fundamental principles of Object-Oriented Programming, as well as in-depth data and information processing techniques. Students will problem solve, explore real-world software development challenges, and create practical and contemporary applications using graphical user interfaces, graphics, and network communications.
3 Credits

MDAN 610

Introduction to Database

This course covers the database concepts that are the foundation and building blocks of sound database design and management. It explains why good database design is critical to the accurate and efficient storage and retrieval of data. The course will explore database design techniques such as database models, database modeling/design tools. The course identifies the functions provided by a database management system to help ensure the integrity of data. It teaches students how to design a database that maximizes data integrity using normalization techniques. It also covers the use of SQL to create and populate tables and retrieve and update data.
3 Credits

Non-Degree-Bearing Courses

MSIN 684, 685, 686

Professional Internship Experience 4, 5, 6

Through practice and participation in professional activities, students will be able to integrate skills presented during course work into real world practice, as well as enhance their awareness of technology in their respective profession. The students will utilize their work as a means of enhancing the educational experience, making on-going strides academically with their professional work. These courses are designed to continue advancement in professional development. These are elective courses which do not count towards the degree. The students will work in a professional environment for a minimum of 240 hours. Students are expected to secure an internship independently. International students are required to apply for CPT for eligibility to work during their internship. Weekly logs and examples of work are required for the successful completion of the internship, and are reviewed by the Faculty Internship Coordinator, upon completion of the internship. The purpose of the internship is to provide students with practical, hands-on experience in their chosen field of expertise to complement their coursework. The Internship MUST be approved in advance by the Program Chair.
1 Credit each