Master of Science in Artificial Intelligence Systems
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
+
2
AI
Electives
6 credits
+
1
Advanced AI
Electives
3 credits
+
2
Program
Core Courses
6 credits
+
1
Capstone
Course
3 credits
=
10
Total Courses
30 credits
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 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 -
MAIN 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
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 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
Any Other Elective Approved by the Dean
Any Advanced 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 -
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 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
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
Program Director
Ferdinand Rivera, M.Ed.
(646) 777 9360
frivera7@touro.edu
New York, NY 10036
Class Locations
3 Times SquareNew York, NY 10036
Are you ready to find out what the future could hold for you?
Please click HERE to request more information.