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Kellogg's AI, ML, and analytics curriculum is built around the observation that managers do not always have a sense of what AI, ML, and analytics can do for them, and data scientists do not always understand enough about a manager's problem to be helpful. What is missing are AI-savvy MBAs who have a passion for business problems and who are so fluent in AI that they can easily converse with and manage teams of data scientists.

As a result, our teaching philosophy in data analytics is to be relentlessly problem driven while taking a deep dive into methods and applications.

Faculty sponsors: Florian Zettelmeyer (Marketing), Brian Uzzi (MORS), Eric Anderson (Marketing).

Foundational Courses in AI and Analytics

These courses provide the statistical and methodological foundations for AI, ML, and analytics.


  • Business Analytics I: 
  • Business Analytics II: 
  • Marketing Research and Analytics: 
  • AI Foundations for Managers: 
  • AI Foundations for Managers: 
  • AI Foundations for Managers: 
  • AI Foundations for Managers: 
  • AI Foundations for Managers: 
Competitive Advantage Courses

These courses teach students how to apply AI, ML, and analytics to different business problems. Students learn new methods as needed to solve the business problems at hand and are required to apply these methods to large real-world datasets.


  • Analytics for Strategy: 
  • Retail Analytics and Pricing: 
  • Strategy Implementation: 
  • People Analytics and Strategy: 
  • Critical Thinking in Digital and Social Media Marketing: 
  • Applied Advanced Analytics: 
  • Customer Analytics and AI: 
  • Human and Machine Intelligence: 
  • Winning with Networks: 
  • Data Analytics with Large Language Models: 
  • Decision Models & Prescriptive Analytics: 
  • Artificial Intelligence and the Future of Work: 
  • Big Data Advanced Analytics Workshop: 
Deep Dive/Experiential Courses

Deep Dive

These courses provide depth in selected areas. In contrast to 鈥渃ompetitive advantage鈥 courses, they can be methods as opposed to problem-focused.

  • Visualization for Persuasion: 
  • Data Exploration: 
  • Technology for Analytics: What a CMO Needs to Know: 
  • Data, Models, and Decisions: 
  • Introduction to Software Development: 

Experiential

These courses allow students to apply their skills from 鈥淐ompetitive advantage鈥 and deep dive鈥 courses to real company situations.

  • Analytical Consulting Lab: 

Apply your analytics skills to live business problems.

For more information, visit Detailed Course Descriptions and Course Recommendations by Career.

Last edited March 18, 2025. For any questions regarding this page, please email kellogg-registrar@kellogg.northwestern.edu.

Contact us about the Evening & Weekend 黑料正能量

Evening & Weekend Application Deadlines

Summer 2025: March 26, 2025
Fall 2025: June 4, 2025
Winter 2026: Sept 24, 2025
Spring 2026: Jan 7, 2026