Master of Science in Business Analytics and AI

2 Year On Campus Masters Program

New York University

Program Overview

New York University's Stern School of Business offers the Master of Science in Business Analytics and AI (MSBAi), designed to help experienced professionals use data and artificial intelligence to improve business decisions and organizational performance. The program combines data engineering, predictive analytics, machine learning, and AI-driven strategy, making it suitable for professionals seeking to advance into analytics and technology leadership roles.

Curriculum Structure (Year-wise)

Year 1: The one-year program is delivered through six intensive in-person modules, supported by online coursework between sessions. Students begin with Introduction to Business Analytics and AI, developing foundational knowledge in data mining, data engineering, and predictive analytics. Further modules cover Applied Statistics, Causal Inference, Machine Learning, Deep Learning, and Generative AI, helping students apply advanced analytical techniques to business challenges.

Year 2: There is no separate second academic year. The six modules are distributed across two calendar years, with the program completed in approximately 12 months. Students advance through Reinforcement Learning, Recommender Systems, Prescriptive Analytics, and AI-driven Decision-Making, strengthening their ability to develop data-driven business strategies.

Focus Areas

Business Analytics, Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, Causal Inference, Predictive Modelling, Prescriptive Analytics, Data Engineering, Data Storytelling.

Learning Outcomes

Apply AI to business decisions, analyse complex datasets, develop predictive models, understand causal relationships, use machine learning techniques, manage data engineering processes, communicate analytical insights, and develop AI-driven business strategies.

Professional Alignment (Accreditation)

AACSB Accreditation: The MSBAi program is accredited by the Association to Advance Collegiate Schools of Business (AACSB).
STEM Designation: The degree is STEM-designated. However, because it follows a part-time modular format, students are not eligible for OPT, including the 24-month STEM OPT extension.

Reputation (Employability & Rankings)

QS Rankings: NYU Stern identifies MSBAi as the highest-ranked part-time Business Analytics master's program in the United States.
Career Progression: 85% of alumni reported a change in job function, employer, or promotion during or after the program.
Career Impact: 89% of alumni reported a positive contribution to their careers from the program.
Industry Connections: Alumni work across leading organizations in finance, consulting, technology, and healthcare, including Deloitte and Medtronic.

Experiential Learning (Research, Projects, Internships etc.)

At New York University, the MS in Business Analytics and AI program is designed to provide students with hands-on experience that bridges the gap between theory and practice. Students engage in real-world projects, utilize cutting-edge technology, and collaborate with industry professionals, ensuring they graduate with the skills and knowledge necessary to excel in the rapidly evolving field of business analytics and artificial intelligence.

The program emphasizes experiential learning through various opportunities, including:

- Capstone Projects: Work on real-world business problems in collaboration with industry partners, allowing you to apply your analytical skills in a practical setting.
- Internships: Gain valuable work experience through internships with leading companies, enhancing your resume and professional network.
- Data Analytics Tools: Access to industry-standard software such as Python, R, Tableau, and SQL, equipping you with the technical skills employers seek.
- Collaborative Learning: Participate in group projects that foster teamwork and communication skills, essential for success in any business environment.
- Research Labs: Utilize state-of-the-art facilities for data analysis and AI research, providing a hands-on approach to learning.
- Industry Partnerships: Engage with guest speakers and industry leaders through seminars and workshops, gaining insights into current trends and practices.
- NYU Libraries: Access extensive resources and databases that support your research and learning, ensuring you have the information you need at your fingertips.

Progression & Future Opportunities

Pursuing an MS in Business Analytics and AI at New York University opens the door to a wealth of career opportunities in a rapidly evolving field. Graduates are well-prepared for roles such as Data Analyst, Business Intelligence Consultant, and AI Product Manager, among others. The demand for skilled professionals in analytics and AI continues to grow, making this program a strategic choice for your future:

- University Services: NYU offers dedicated career services, including personalized career coaching, resume workshops, and networking events with industry leaders to help you secure internships and job placements.
- Employment Stats and Salary Figures: Graduates from the program have reported an impressive employment rate of over 90% within six months of graduation, with starting salaries averaging around $85,000, depending on the role and location.
- University–Industry Partnerships: NYU has established strong partnerships with leading companies such as Google, IBM, and Deloitte, providing students with access to real-world projects and internship opportunities that enhance learning and employability.
- Long-term Accreditation Value: The program is accredited by the Association to Advance Collegiate Schools of Business (AACSB), ensuring that your degree holds significant value in the job market and is recognized globally.
- Graduation Outcomes: Alumni have gone on to work at top firms and have reported high levels of job satisfaction, often advancing to leadership positions within just a few years of graduation.

Further Academic Progression: After completing your MS in Business Analytics and AI, you may choose to further your studies by pursuing a Ph.D. in a related field, such as Data Science or Information Systems. This path can lead to academic positions or advanced research roles, allowing you to contribute to the field at a higher level. Additionally, you might consider obtaining professional certifications in specialized areas like machine learning or data visualization to enhance your expertise and marketability.