You will receive an answer in your candidate space within 2 months of the closing date for the application session. Special cases: please refer to the "Cost of studies" section of the FAQsįind out more about scholarships Applications and admission dates.Engineer students enrolled in one of the five member schools of Institut Polytechnique de Paris (Ecole polytechnique, ENSTA Paris, ENSAE Paris, Télécom Paris and Télécom SudParis): 159€.Two academic references (added online directly by your referees).You will need to provide the following documents: Language prerequisitesĪpplications can be submitted exclusively online. master sophisticated techniques both theoretically and in practiceĪdmission requirements Academic prerequisitesĬompletion of the first year of a Master in mathematics at Institut Polytechnique de Paris or equivalent in France or abroad.gain a comprehensive training in the various disciplines constituting data science, with a strong emphasis on the mathematics and statistics methodology.become experts on statistical learning and artificial intelligence.At the end of the year, both the results at the chosen courses and the professional project are evaluated to validate the Master.įrom the next year, no more apprenticeship program. In particular, these skills are developed through practical projects and data science competitions. At the end of the training, the students have acquired skills in mathematics of statistical learning, in deep learning, reinforcement learning, optimization, and big data infrastructures among others. The objective of the Master in Datascience is to train experts in this field. You get to learn a lot of different techniques and interact with smart folks from. This is a hybrid profile requiring a solid background in mathematics and statistics, mastery of data management and processing tools and infrastructure, as well as curiosity and a thirst to understand. I am a 2015 graduate of the Data Incubator and it was a great experience. Data scientists are in charge of retrieving, storing, organizing, processing this mass of information to create value. Today, major players in the world of business are increasingly aware of the potential of their data and are looking for ways to extract as much useful information as possible.
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