Data, Models and Decisions in Business Analytics

Course 2 of 4: MicroMasters Program in Business Analytics 12 Weeks 8–10 hours per week recommended

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About this course

In today’s world, managerial decisions are increasingly based on data-driven models and analysis using statistical and optimization methods that have dramatically changed the way businesses operate in most domains including service operations, marketing, transportation, and finance.

The main objectives of this course are the following:

  • Introduce fundamental techniques towards a principled approach for data-driven decision-making.
  • Quantitative modeling of dynamic nature of decision problems using historical data, and
    Learn various approaches for decision-making in the face of uncertainty
  • Topics covered include probability, statistics, regression, stochastic modeling, and linear, nonlinear and discrete optimization.

Most of the topics will be presented in the context of practical business applications to illustrate its usefulness in practice.

What you’ll learn

  • Fundamental concepts from probability, statistics, stochastic modeling, and optimization to develop systematic frameworks for decision-making in a dynamic setting
  • How to use historical data to learn the underlying model and pattern
  • Optimization methods and software to solve decision problems under uncertainty in business applications


Undergraduate probability, statistics and linear algebra. Students should have working knowledge of Python and familiarity with basic programming concepts in some procedural programming language.


Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

Meet Your Instructors

Vineet Goyal

Associate Professor, Industrial Engineering and Operations Research at Columbia University
Vineet Goyal is an Associate Professor in the Industrial Engineering and Operations Research department at Columbia. He received his PhD in Algorithms, Combinatorics and Optimization (ACO) in 2008 from Tepper School of Business, CMU. Before joining Columbia, he spent a couple of years as a postdoctoral associate at the Operations Research CenterMIT working with Dimitris Bertsimas.

Experience Level


Learning Partner

Columbia University

Program Type



Business & Management
Advanced Business Harvard X-Series