The objective of this course is to analyze real-world situations in which a significant competitive advantage can be obtained through large-scale data analysis. Particular attention is given to the actionable insights that can be derived from data and the potential pitfalls associated with data-driven approaches. Students are challenged to formulate business-relevant questions and solve them through the manipulation of large data sets. The course showcases applications from diverse domains, including advertising, eCommerce, finance, healthcare, marketing, and revenue management. Students will learn to apply technologies such as Artificial Intelligence and Python to analyze data sets and generate knowledge that informs decision-making. The course covers the fundamentals of data-driven decision-making, including statistical modeling, machine learning, and experimental design. Students are expected to integrate these topics with their existing proficiency in mathematical notation, algebra, calculus, probability, and basic statistics.
3 units · GSB Letter Graded
The objective of this course is to analyze real-world situations in which a significant competitive advantage can be obtained through large-scale data analysis. Particular attention is given to the actionable insights that can be derived from data and the potential pitfalls associated with data-driven approaches. Students are challenged to formulate business-relevant questions and solve them through the manipulation of large data sets. The course showcases applications from diverse domains, including advertising, eCommerce, finance, healthcare, marketing, and revenue management. Students will learn to apply technologies such as Artificial Intelligence and Python to analyze data sets and generate knowledge that informs decision-making. The course covers the fundamentals of data-driven decision-making, including statistical modeling, machine learning, and experimental design. Students are expected to integrate these topics with their existing proficiency in mathematical notation, algebra, calculus, probability, and basic statistics.
Offered in Winter 2026 at Stanford University.