MS in AI for Business Curriculum

A track tailored to your interests

Olin’s AI for Business degree is not a broad, shallow look at AI — we’ve created three tracks that can assist with strategic decision-making in specific business use cases.

All tracks include foundational courses about vital tools and concepts (including Introduction to Python and Data Science, Generative Artificial Intelligence, and Deep Learning for Prediction of Business Outcomes).

Then, each track adds a tightly focused set of courses building on key AI applications that will vary based on students’ interests and previous business experience:

Finance

From algorithmic trading and risk assessment to market forecasting and predictive models, AI is remaking the world of finance. Demand is particularly strong for AI-skilled financial analysts and risk analysts.

Sample courses:

• Advanced AI in Finance

• Financial Technology — Methods and Practice

• Seminar in AI-Driven Finance

Marketing

Communications fields are undergoing rapid transformation, relying on AI for customer service communication, campaign optimization, and more. Opportunities abound for product managers, content managers, and marketing analysts.

Sample courses:

• Analytics-Driven Brand Management

• AI-Driven Customer Analytics

• A/B Testing in Business and Social Science

Technical

Every business sector is increasingly dependent on AI for a range of applications. The AI for Business technical track is designed for students who already have a business education or work experience and are looking to upskill themselves for new AI-driven expectations. Demand for these skills exists across many traditional business roles as well as new ones being continuously created in the AI-driven business marketplace, such as prompt engineers, AI compliance officers, and human-AI interaction designers.

Sample courses:

• Ethics and Responsible AI in Business

• Business-Driven Explainable AI

• Data Visualization for Business Insights

Required Courses for all Tracks

Total Credits: 30

• Introduction to Python and Data Science

• Machine Learning Tools for Prediction of Business Outcomes

• Generative Artificial Intelligence

• Deep Learning for Prediction of Business Outcomes

• Deep Reinforcement Learning with Application in Business

• AI-Driven Causal Inference with Observational Data

Note: Additional required courses and elective options will vary by track.