Data, Models and Decisions in Business Analytics
date_range Débute le 17 septembre 2018
event_note Se termine le 22 décembre 2018
list 12 séquences
assignment Niveau : Avancé
chat_bubble_outline Langue : Anglais
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Les infos clés

credit_card Formation gratuite
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timer 96 heures de cours

En résumé

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.

  • 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

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Les prérequis

Undergraduate probability, statistics and linear algebra.

Students should have working knowledge of Python and familiarity with basic programming concepts in some procedural programming language.

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Le programme

  • Introduction to Probability: Random variables; Normal, Binomial, Exponential distributions; applications
  • Estimation: sampling; confidence intervals; hypothesis testing
  • Regression: linear regression; dummy variables; applications
  • Linear Optimization; Non-linear optimization; Discrete Optimization; applications
  • Dynamic Optimization; decision trees
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Les intervenants

Vineet Goyal
Associate Professor, Industrial Engineering and Operations Research
Columbia University

Costis Maglaras
David and Lyn Silfen Professor of Business
Decision, Risk and Operations Division, Columbia Graduate School of Business

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Le concepteur

For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.
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La plateforme

EdX est une plateforme d'apprentissage en ligne (dite FLOT ou MOOC). Elle héberge et met gratuitement à disposition des cours en ligne de niveau universitaire à travers le monde entier. Elle mène également des recherches sur l'apprentissage en ligne et la façon dont les utilisateurs utilisent celle-ci. Elle est à but non lucratif et la plateforme utilise un logiciel open source.

EdX a été fondée par le Massachusetts Institute of Technology et par l'université Harvard en mai 2012. En 2014, environ 50 écoles, associations et organisations internationales offrent ou projettent d'offrir des cours sur EdX. En juillet 2014, elle avait plus de 2,5 millions d'utilisateurs suivant plus de 200 cours en ligne.

Les deux universités américaines qui financent la plateforme ont investi 60 millions USD dans son développement. La plateforme France Université Numérique utilise la technologie openedX, supportée par Google.

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