Master of Business Analytics and AI

Destined TU Break Ceilings

Businesses today thrive on data, relying on skilled analytics professionals to turn insights into actionable strategies. Tulane University’s Master of Business Analytics and AI program equips you with expertise in strategic analysis, risk management, and problem-solving—preparing you to navigate the evolving business landscape with confidence.

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Master of Business Analytics & AI at a Glance

Program Start

August

Program Length

2 or 3 semesters

Class Schedule

In person

Admissions Deadline

1st Round: November 1
2nd Round: February 1
Final Round: May 1

Specializations

Accounting and Finance
Energy
Marketing

Career Outcomes

significant advantage and the experience, knowledge, and skills employers worldwide are seeking

Why Enroll in Our Business Analytics and AI Program

100%
employment within 3 months, 2025

#54
Best Graduate Schools — U.S. News & World Report, 2025

30
credit hours

#58
Best Business Schools List — Bloomberg, 2024

Your Journey TU Achieve More Starts Here.

Admissions Requirements

Learn about Freeman's admissions process, application requirements, and deadlines.

Curriculum

Explore course overview and unique specializations / concentrations offered.

Tuition & Scholarships

Discover merit-based scholarships opportunities and financial aid options.

Student Success

Envision the ROI you can unlock with a Freeman graduate degree.

Explore the Master of Business Analytics and AI Program

From customer insights and risk management to economic outlooks, businesses in today’s world run on data. That means they depend on detail-oriented business analytics professionals to translate data insights to actionable strategies. When you earn a Master of Business Analytics and AI from Tulane University’s Freeman School of Business, you’ll gain expertise in strategic analysis and planning, risk management and problem-solving to enter your career with confidence.

Benefits of a Master of Business Analytics and AI Degree

The Master of Business Analytics & AI curriculum doesn’t just cover the essential skills listed in every analytics job posting. The courses in our business analytics degree program dive deeper to cover skills that potential employers may not even know that they need. Through hands-on experience with real data sets and real companies, you’ll be career-ready as you present to industry experts in the fall and complete a semester-long project addressing a current business problem for a local company in the spring.

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Skills You Will Learn

Machine Learning & AI Applications: Apply advanced machine learning algorithms, large language models and AI tools to solve complex business problems.
Predictive Analytics & Forecasting: Build and validate models for financial forecasting, risk assessment, and market trend analysis.
Customer & Behavioral Analytics: Analyze customer behavior patterns and preferences to inform marketing and strategic decisions.
Data Visualization & Storytelling: Design clear, impactful visual narratives that translate analytical insights into persuasive business communications.
AI-Enhanced Programming & Tools Integration: Gain hands-on experience using LLM APIs and AI coding platforms such as OpenAI, Claude, and Google Colab to enhance analytical workflows.

Core Competencies

Cross-Functional Business Applications: Integrate analytical expertise across domains such as finance, marketing, risk management, and consulting to create enterprise value.
Data-Driven Strategic Decision-Making: Transform complex datasets into actionable insights that guide organizational strategy and performance.
Analytical & Critical Thinking: Approach business challenges systematically, evaluate data integrity, and apply rigorous reasoning to reach sound conclusions.
Applied Experiential Learning: Collaborate with industry partners on real-world analytics projects, applying advanced methods, and tools to deliver business solutions.
Ethical & Responsible AI Practice: Evaluate the ethical implications of AI and data usage, ensuring transparency, fairness, and accountability in analytics applications.