Curriculum
Program at a Glance
All full-time MS programs are STEM-designated
AugustProgram Start | 11Courses | 9 or 16Months |
Internship vs. Non-Internship
Students in the Full-Time MSAIB program can select either an internship or non-internship track based on their career plans. During the admissions process, counselors will help you determine the right path. After enrollment, the Benet Career Management Center will continue to support your decision as your goals evolve. For further details, check out our course catalog.
Internship Track
16 Months
Designed to allow time for a summer internship, this track supports students seeking U.S. business experience and additional time for career exploration.
Non-Internship Track
9 Months
For students ready to enter the workforce directly after graduation, this accelerated option allows for a shorter program timeline.
Core Courses
- CIS 433: AI and Deep Learning
This course introduces the field of AI to business students with a particular emphasis on deep learning, which is driving the current AI revolution. The course consists of three modules:
1. Foundations of AI and Deep Learning – Establishes the foundation of AI and deep learning.
2. Neural Network Architectures – Introduces major neural network architectures widely used in practice.
3. Generative AI – Touches on generative AI, which is particularly promising in recent years.
The course emphasizes experiential learning and contains many hands-on projects using TensorFlow broadly and Keras in particular.- CIS 455: AI Business Project
In CIS455, students will engage in an AI-focused business project, bringing together the program’s conceptual frameworks, analytical methodologies, and technical skills. Students will work on real world projects that sponsoring organizations will provide. Student project teams will work with faculty coaches and any other relevant technical experts to complete their work for presentation and delivery to the client at the end of the course. These projects will require and further develop the AI, analytics, communication, and leadership skills learned throughout the program.
- GBA 424: Analytics Design and Applications
The course will introduce and apply frameworks related to answering these questions. The course will use a series of real-world cases and examples involving managerial decisions to connect analytics to real world problems. These cases will take the students through an active learning process that builds on and extends the skills and knowledge gained in previous courses. The course focuses heavily on “soft” skills related to structuring complex problems, decision-making with imperfect information, and designing analysis to address analytics research questions. The course also reinforces and expands on “hard” skills related to data wrangling, programming, descriptive, predictive, and causal analytics, as well as introducing some unsupervised learning methods. The course will leverage software tools such as sql, Python, and Tableau.
- GBA 462P: Core Statistics for MS Students Using Python
This course equips MS students with statistical skills necessary for data-driven decision making. The course covers central tendency and variability, probability, binomial and normal distributions, standard scores, hypothesis testing, z and t tests, ANOVA, correlation and regression, and non-parametric tests.
- GBA 464: Programming for Analytics
This course provides a foundation in programming within the Python environment. Traditional programming concepts (operators, data structures, control structures, repetition, and user-defined functions) will be central to the learning objectives, but the concepts will be taught in the context of marketing and business analytics problems related to data management and visualization. In addition to high-level programming, the students will gain a foundational understanding of how data are organized and pulled from databases, including the querying process that turns raw data into the kinds of datasets that more advanced analytics tools leverage. The course involves hands-on tutorial assignments with practical pattern matching as well as less structured programming assignments, where the students are expected to write their own programs.
- GBA 478: Intro to AI and Business
GBA478 covers the application of generative AI technologies across diverse business contexts. The course will help you understand how to integrate Generative AI into today’s business workflows, providing frameworks to decide when and how to use it effectively. You’ll gain hands-on experience designing Generative AI tools to create business value and programming basic LLM-driven applications in Python. Finally, the course will ask you to become conversant with the big questions about Generative AI, to debate the moral, philosophical, and ethical challenges inherent in these systems and technologies.
- GBA 479: Generative AI and Business Applications
This course covers the design and development of Generative AI-enhanced business applications. We will discuss a framework for integrating Gen AI tools and capabilities into business processes, tasks and workflows. Students will learn how to program with Gen AI tools and LLMs using Python and APIs, including methods for dynamic task automation and workflow coordination using agentic design. The course also covers the use of Retrieval-Augmented Generation (RAG) to access private knowledge bases built on organizational data. By the end of the course, students will be equipped with the technical and conceptual skills to design and build generative AI applications tailored to modern business needs.
- MGC 461: Professional Communication
MGC 461 is based on classical principles of argument and persuasion and current communication research that reveals the keys to having influence in a global business world. Its goal is to develop professional-level presentation skills, individually and in teams. The course is performance based; all class sessions require students to speak and interact extensively. Over two mini-semesters, students develop professional presentation skills through four individual and two team-based speaking assignments, for which they receive extensive, individualized feedback. They also learn a systematic process for assessing their own communication, and for giving feedback to others. At the end of the course students will have developed skills key to success in any field: the ability to adapt effectively to a given audience, and to express ideas with an appropriate combination of logic and feeling.
AI-Focused Capstone Project
The AI Business Project (CIS 455) challenges students to apply AI, analytics, and communication skills to real-world business problems. Sponsored by industry partners and guided by faculty coaches, project teams deliver data-driven solutions that demonstrate both technical depth and strategic impact.
Electives
Choose three of the following.
- CIS 417: Introduction to Business Analytics
This course focuses on how analytics can support/improve business operations. It covers the fundamental principles and techniques of business analytics, in particular supervised and unsupervised machine learning methods, and uses real
world examples and cases to illustrate these. The objective is to train students to approach business problems data-analytically—translate business problems
into one or more related analytic problems; identify the appropriate techniques to solve these problems; and critically evaluate the results and their impact on business performance. The material will be presented in an intuitive manner, with the goal of making students intelligent consumers of these widely applicable techniques. However, hands-on learning using appropriate software is required to achieve sufficient mastery of the material.MBA Prerequisite: GBA 412
- CIS 431: Big Data
This course is designed to provide students with concepts and skills in managing data using traditional and cloud based systems. The course covers theory of database systems, data manipulation techniques, data integration and cleaning, and working with modern and advanced data architectures. The class covers both theory and hands on activities using Microsoft Access, SQL, Tableau and R. Microsoft Access, SQL, Tableau and R may be used extensively in class, for assignments and exams.
- CIS 432: Machine Learning for Business Analytics
This course aims to train practitioners of analytics methods to construct, evaluate, and apply machine learning (ML) models in a variety of business applications using modern tools. The course covers programming tools for handling data, computational frameworks, cloud platforms, and an array of advanced ML algorithms. The course emphasizes hands-on work through class exercises, homework assignments, and projects. The course is self-contained, but basic programming skills are required.
- CIS 434: Social Media and Text Analytics
This course draws on a unique blend of social media strategies and the rapidly evolving information technologies supporting these strategies. We will discuss issues related to the monitoring and analyzing of social media for companies in different industries. The learning objectives of this course include: (1) gaining a deeper understanding of social media and its implications in the business world;(2) becoming comfortable with text data; and (3) being able to understand and apply several commonly used methods to analyze text data.
- CIS 438: Agentic AI Application
This course introduces the basics of developing web-based AI applications with foundation models. The primary goal is to prepare students for projects that require not only the analysis of data or the use of modern AI techniques, but also the creation of well-designed and fully functional user interfaces supporting a medium number of concurrent users. The secondary goal is to help students develop a personal branding site showcasing their knowledge base and skill sets. The course has three components.
1) In the first component, we review large language models, with a focus on open-source foundation models.
2) In the second component, we learn Node.js, a cross-platform, open-source JavaScript runtime environment, and NoSQL database.
3) The third component is a capstone project using the first two components to develop a web-based AI chatbot.- CIS 467: Data Management and Warehousing
This course focuses on database design, management, and warehousing concepts to support AI and analytics efforts. The course introduces ER diagrams, SQL programming and related frameworks for data retrieval and transformation as well some advanced SQL features such as user-defined functions, triggers and procedures.
- GBA 468P: Prescriptive Analytics with Python
GBA468 expands and develops the students’ analytical toolkit to include prescriptive analytics methodologies for managerial decision-making. The coursework follows the FACt approach to business problem solving and will cover diverse applications in operational management, supply chain analytics, marketing, and finance. Modeling techniques covered include: Decision tree models Constrained optimization models Monte Carlo simulation The course will be taught primarily using Python.
Apply for the term that fits your goals—Simon offers multiple entry points.
Merit-based scholarship available. No GMAT/GRE Score required. No previous coding experience required.
Spring 2026 Deadline: | Fall 2026 Deadline: |
“Our MSAIB program prepares students for careers at the forefront of our AI-transformed business world through its innovative combination of coursework in applied AI, core stats and analytics, fundamental business concepts, and experiential, case-based project work. Students graduate with a portfolio of AI solutions developed through hands-on, business-focused projects, that demonstrate their ability to design and implement intelligent solutions to business challenges. Our curriculum bridges the gap between technical knowledge and real-world business impact, giving students the tools to succeed, and to lead, in an evolving business landscape.”
Simon’s MS in AI in Business program is STEM designated.
Simon's specialized master's program in AI in Business meets all the requirements for a STEM-designated program. The STEM (Science, Technology, Engineering, Mathematics) designation signals analytical rigor to employers and also offers international students the opportunity to extend their Optional Practical Training (OPT) by 24 months—for up to three full years of US work eligibility without and H-1B visa.