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.
These courses provide the statistical and methodological foundations for data analytics.
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 problems at hand and are required to apply these methods to large real-world datasets.
Deep Dive Courses:
These courses provide depth in selected areas. In contrast to “Competitive Advantage” courses, they can be methods as opposed to problem-focused.
These courses allow students to apply their skills from “Competitive Advantage” and Deep Dive” courses to real company situations.
Faculty sponsors: Florian Zettelmeyer
(Marketing), Brian Uzzi
(MORS), Eric Anderson
Business Analytics I
Business Analytics II
2 Competitive Advantage
Analytics for Strategy
Retail Analytics and Pricing
People Analytics and Strategy
Critical Thinking in Digital & Social Media Marketing
Applied Advanced Analytics
Customer Analytics and AI
Human and Machine Intelligence
Social Dynamics & Network Analytics
Descriptive and Predictive Analytics in R
Decision Models and Prescriptive Analytics
3 Deep Dive
Visualization for Persuasion
Technology for Analytics: What a CMO Needs to Know
Data, Models, and Decisions
Introduction to Software Development
Analytical Consulting Lab
Apply your analytics skills to live business problems.
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