Course Map

VIDEO: Watch to learn about our rigorous curriculum, developed by visionary researchers with ongoing input from industry leaders.

Kellogg's data analytics curriculum is built around the observation that managers do not always have a sense of what 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 analytics-savvy MBAs who have a passion for business problems and who are so fluent in data analytics 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.

To determine which data analytics courses to take, students should start by determining the level of expertise they’d like to achieve.

To prepare for learning analytics, students should take the Foundational courses. These courses provide the statistical and methodological foundations for data analytics. All students — regardless of their interest in data analytics — are required to take these courses.

To obtain a working knowledge of analytics, students should also take Competitive Advantage courses. These courses teach students how to apply data analytics to different business problems. Students learn new methods as needed to solve the business problem at hand and are required to apply these methods to large real-world datasets.

To become fluent in analytics, students should also take Deep-Dive courses. These courses provide depth in methods. Students should also consider taking an Experiential course where they can apply their analytics skills to real business problems.

Students may use this guide to determine which courses are most relevant to their chosen career path.

data analytics curriculum
1 Foundational
Business Analytics I
DECS 430-5
Business Analytics II
DECS 431
Marketing Research
MKTG 450
2 Competitive Advantage
Analytics for Strategy
STRT 469
Retail Analytics
MKTG 462
Sports and People Analytics
MORS 910-5
People Analytics and Strategy
STRT 440
Customer Analytics
MKTG 482
Social Dynamics & Network Analytics
MORS 457
Digital Marketing Analytics
MKTG 955
Human and Machine Intelligence
KACI 950-5
Health Analytics
HEMA 940-5
3 Deep Dive
Visualization for Persuasion
KACI 925-5
Technology for Analytics
KMCI 930-5
Programming for Analytics
KMCI 935-0
Data Exploration
DECS 922-5
Analytical Consulting Lab
MECN 915
Data Analytics Decisions
KMCI 940
Apply your analytics skills to live business problems.