Artificial Intelligence for Business

The Artificial Intelligence for Business major is designed to address two broad topics: (1) the (more) technical understanding of methods and how they are being applied by firms to solve business problems and (2) the (more) conceptual understanding of how the technology impacts firms and society, including economic, social, and ethical issues that AI deployment introduces. 

Reflecting this conceptualization, the major has two pillars, F&I: 

• Foundations of AI in Business (or F)
• Impact and Ethical Implications of AI in Business (or I)

Courses from Pillar F cover foundational skills needed to understand, work with, and/or evaluate AI systems. Such courses can cover, but are not limited to, subjects such as data engineering, data science, statistics, machine learning, or neuroscience. 

Courses from Pillar I cover the business, economic, legal, ethical, psychological, or societal impact of AI. 

REQUIREMENTS FOR MAJOR 

The major in Artificial Intelligence for Business requires a total of 4 CU. 

• Courses taken on a pass/fail basis cannot be counted toward the major.
• A maximum of 1 CU of an Independent Study Project (ISP) can count toward the major with faculty advisor approval.
• A maximum of 1 CU of courses outside of Wharton may be considered with faculty advisor approval.

Students must complete the following courses, one from each pillar, for a total of 1.5 CU: 

Pillar F 

STAT 7230: Applied Machine Learning in Business (1 CU) 

Pillar I 

LGST 6420: Big Data, Big Responsibilities: Toward Accountable Artificial Intelligence (0.5 CU) 

The remaining 2.5 CU must be taken as follows:

Pillar F – Complete an additional 1 CU: 

FNCE 7370: Data Science for Finance
FNCE 7800: FinTech
HCMG 8530: Management and Strategy in Medical Devices and Technology
HCMG 8570: Healthcare Data and Analytics
MKTG 7120: Data and Analysis for Marketing Decisions
MKTG 7370: Introduction to Brain Science for Business
MKTG 7680: Contagious: How Things Catch On
MKTG 9560: Empirical Models in Marketing – Part A*
OIDD 6620: Enabling Technologies**
OIDD 7770: Introduction to Python for Data Science
STAT 7010: Modern Data Mining
STAT 5810/OIDD 5810: Convex Optimization for Statistics and Data Science*
STAT 5850: Foundations of Deep Learning with Applications*  

Pillar I – Complete an additional 1.5 CU: 

HCMG 8580: Health AI
MGMT 7310: Technology Strategy
MGMT 8020: Innovation, Change, and Entrepreneurship
MKTG 7340: Idea Generation and the Systematic Approach for Creativity
MKTG 7790: AI in Our Lives: The Behavioral Science of Autonomous Technology
OIDD 6130: Online Business Models and the Information-Based Firm**
OIDD 6670: A.I., Business, and Society

* These courses are PhD-level courses and are registered via Path@Penn. As such, students are required to adhere to the overall process and add/drop deadlines stipulated by the Wharton Doctoral Program. Wharton PhD courses will count towards the 15 CU minimum of Wharton coursework but are not graded on the MBA curve and will not be factored into a student’s Wharton GPA. 

** OIDD 6130 and OIDD 6620 cannot count towards both the AI for Business major and the OIDD flexible core requirement.