Today, it is clear that all management students must be trained in Big Data and its algorithms, which have become essential in all companies.
Like many management courses, this course will expose the stakes, opportunities, threats and consequences of Big Data for the management of companies. However, beyond the simple simplistic speeches on the subject, it is about giving students a real opportunity to go deeper into the subject.
After completing this course, students will be able to interact with engineers in a multidisciplinary team of data scientists. They will master all the basics of the R language. They will be able to implement algorithms such as those used in GAFA recommendation systems, or to predict consumer purchases using decision trees, random forests or Bayesian models.
A group project will be conducted under the supervision of the professor for a company. This will typically be a 'market basket analysis' for a business. It will be the subject of a report.
This study will be valued in the CV alongside the knowledge acquired from R.
The course does not require any specific prior knowledge.
Realisation of algorithms with the R software
Predicting consumer purchases using decision trees, random forests or Bayesian models
Group project of the 'market basket analysis' type under the supervision of the teacher for a company
Alexandre Steyer is Professor of Universities and director of the Master in International Strategy and Economic Intelligence. He is also the founder and former director of the PRISM research laboratory. After joining the ENS (Ecole Normale Supérieure) in Paris, Alexandre Steyer successively obtained a license, a master's degree in physics, a DEA in quantum physics as well as a doctorate in statistical physics (1991). Upon leaving the ENS, he joined the inter-ministerial body of telecommunications as an engineer and undertook, in parallel, a thesis in management sciences at HEC. The defense of his thesis, entitled "The theory of avalanches", earned him the 1993 HEC Foundation Prize. His research themes are Social Physics and Data Science.