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:
Students may join any class session on campus or online. Professors and students are interacting in real time during the class session, with some students in the classroom and the rest joining online. All students can later re-watch the recording of any class session on their own time to reinforce that evening’s concepts. F1 international students must follow the guidance of the Department of Homeland Security regarding classroom presence and can contact us for more information.Program Requirements
4
AI
Core Courses
12 credits
+
3
AI
Electives
9 credits
+
2
Program
Core Courses
6 credits
+
1
Capstone
Course
3 credits
=
10
Total Courses
30 credits
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