MASTER IN BIG DATA ANALYTICS FOR BUSINESS
| Lugar de estudios | Francia, paris |
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| Tipo | Master, tiempo completo |
| Idioma de estudio | inglés |
| Colegiatura | 18.900 € por año |
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| Requisitos de idioma | inglés |
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| Otros requisitos | Se debe proveer al menos 2 referencia(s). |
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| Más información |
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Resumen
The Master in Big Data Analytics for Business is a 4-term program completely taught in English which aims at training data scientists.
Participants are exposed to the leading-edge fundamentals in data-driven decision-making by extracting knowledge and insights from Big Data. They will learn how to solve managerial problems by critically asking questions in the spirit of ‘What do we know?’ (Data driven) rather than ‘What do we think? (Gut feeling).
Estructura del curso
The Master in Big Data Analytics for Business is designed to help participants mastering the business knowledge, the methods and the analytical tools to convert BIG data into BIG insights in marketing, finance and operations.
The program is offered on a full-time basis and consists of 3 terms of academic courses and a professional experience. The curriculum is developed around core modules in business, technology, and methodology, as well as specialized courses in marketing, finance, and operations.
In a connected world, data provide companies with the opportunity to align their marketing, finance and operations strategy with objective facts and figures. Participants will learn how to become data-driven managers, and will be able to spot analytical opportunities in a given business context.
Oportunidades profesionales
Participants will acquire the skills to discover key information by reviewing company data and taking into consideration the relevent business context. They will become decision makers with strong fundamentals in business and analytics.
They are trained to become data scientists and could work as:
Digital/Online Marketers;
Web Analysts;
Consumer Intelligence Experts;
Market Researchers;
Database Marketers;
Customer Insights Managers;
Financial Analysts;
Credit Scoring Analysts;
Fraud Detection Analysts,
or in any other data-driven related positions.