Master of Science in Artifical Intelligence

Study Synchronously Online or On Campus: It's Your Choice STEM-Certified Program

The Artificial Intelligence Systems program at the Touro University Graduate School of Technology is designed to provide students with the comprehensive knowledge and practical skills needed to excel in the rapidly growing field of AI. With an emphasis on both generative and predictive AI, the curriculum equips students to integrate AI solutions into complex systems and business processes, addressing real-world challenges across various industries. Whether you're looking to master the technical aspects of AI or seeking to lead AI initiatives, this program offers a blend of theoretical and hands-on learning that prepares graduates for success in a range of cutting-edge roles.

Students will gain expertise in key areas such as large language models (LLMs), AI analytics, and AI systems design, while also delving into the ethical, legal, and social implications of AI technologies. Through courses focused on AI tools and methodologies, project management, and system integration, students will develop the ability to manage and implement AI projects across multiple domains, including healthcare, finance, autonomous systems, and more.

The program's flexible structure allows students to tailor their learning through elective courses in areas like visual analytics, digital marketing, and data visualization, ensuring they are well-equipped to meet the demands of a variety of AI-centric careers. Whether studying online or on campus, students will benefit from a dynamic and supportive learning environment that fosters critical thinking, innovation, and leadership.

Career options include:

MODE OF DELIVERY FOR ARTIFICIAL INTELLIGENCE COURSES:

Program Requirements

Artificial Intelligence Required Courses

AISN 610

Foundations of Artificial Intelligence

Gives a broad overview of the history and concepts of AI, and foundational skills in using AI tools and systems.
3 Credits

AISN 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

AISN 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 emphasizes practical applications, including how to effectively collect, analyze, and interpret data, while ensuring students develop a keen understanding of model assessment and selection to inform strategic decisions.
Prerequisite: Basic Statistics.
3 Credits

AISN 625

AI Systems Design

Students learn how to design systems and processes that use AI as a key component. This course emphasizes the design, implementation, and management of AI-driven processes across various applications, including, but not limited to autonomous systems, predictive analytics, and intelligent interfaces. Students will explore how to practically use 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

Artificial Intelligence Elective Courses (Choose 3)

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 across different industries, focusing on iteratively deriving solutions through static and interactive dashboards. Students will gain hands-on experience with the latest cloud BI software, ingesting data and structuring relations between disparate sources. Working in agile-like weekly sprints, students will learn to identify patterns and anomalies, conduct prescriptive analyses, and effectively 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 profoundly reflect customers’ needs, expectations, and behaviors
• measure real digital media ROI: sales, leads, and customer satisfaction
• track the performance of all paid, earned, and owned digital channels
• leverage digital data beyond PR and marketing: for strategic planning, product development, and HR
• start optimizing digital content in real time
• implement advanced tools, processes, and algorithms for accurately measuring influence
• make the most of surveys, focus groups, and offline research synergies
• focus new marketing investments where they’ll deliver the most value
• identify and understand important audiences across the digital ecosystem

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 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 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

AISN 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

AISN 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

AISN 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

Any Other Elective Approved by the Dean

M.S. in Artificial Intelligence Core 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

Information Technology 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

M.S. in Artificial Intelligence Capstone Courses (Choose 1)

AISN 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

AISN 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

Artifical Intelligence 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 607

Effective Oral and Written Communication for Managers

Emphasizes the importance of good communication skills for corporate managers in the business world. This course identifies and reviews the foundations of business communication - listening, speaking, writing, and reading - and broadens students' experience by building communication skills using technologies and practical business applications. The goal of this course is for students to become confident, flexible, and resourceful communicators in the competitive intercultural global business community.
3 Credits

MSIN 511

Technology Concepts and Essentials

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

Introduction to Statistics

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 608

Introduction to Programming

This course introduces students to problem solving techniques used in programming. Students will learn object-oriented and event driven programming concepts including language constructs, logical structures, file management and error trappings. Students will program in the Alice 2.3 3-D Programming Language Environment that was specifically developed to make learning programming more accessible and exciting to students. Students will learn how to create and use objects and their properties and methods, as well as how to write code for custom object methods. Students will utilize programming control structures such as loops, selection structures, methods, and classes.
3 Credits

MDAN 609

Introduction to Analytical Processes (Excel)

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

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 using Microsoft Visio. The course identifies the functions provided by a database management system to help insure the integrity of data. It teaches students how to design a database that maximizes data integrity using normalization techniques. Students will use MS Access interface to create and populate a database. It also covers the use of SQL to create and populate tables, retrieve and update data.
3 Credits