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LUISS Business School > id corso 4614

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Master in Big Data Management

LUISS Business School


stage, tirocinio

modalità erogazione
formazione in aula

borse di studio, riduzioni

non previste

programmi pubblici
corso non finanziato

termine delle iscrizioni
11 marzo 2019

inizio delle lezioni
25 marzo 2019

12 mesi

costo di partecipazione
14.000 Euro

laureati di secondo livello,laureati di primo livello

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The program prepares students to work effectively with heterogeneous, real-world data, training them to become experts in extracting useful insights for business. 

The Master in Big Data Management program prepares students to work effectively with complex, real-world data and to create value from it.
Big Data Management focuses on improving the understanding of customer patterns to increase business and improve profitability.  Working in big data management requires a hybrid set of competencies: computer expertise with a good knowledge of advanced statistical techniques, a thorough understanding of the business world and excellent communication skills. Finding this set of competencies in a single person is rare. They need to be developed with the right mix of classroom and field learning.
The Master in Big Data Management curriculum is designed to prepare students to create analytical models and interpret them from a business-oriented perspective. It prepares young professionals to pursue a career as a data scientist or business analyst for companies including large industrials, consulting firms and marketing specialists.



The Master provides students with 60 ECTS credits. It teaches them how to harness large amounts of data, design analytical models and interpret them to optimize business processes.

Among the competences provided:

  • Skills to collect, process and extract value from large and diverse data sets
  • Capacity to work with different computing tools in order to address complex problems
  • Imagination to understand, visualize and communicate findings to non-data scientists
  • Ability to create data-driven solutions that boost profits, reduce costs and improve efficiency


Learning methods and key coures 

  • Top managerial education
  • Combination of lectures and labs
  • Field project Econometrics
  • Linear algebra/Multivariate calculus
  • Machine Learning
  • Programming: Hadoop/Spark, Python, R, SQL
  • Statistics


Target Audience

The Master is targeted for students with a BA or MS in Economics, Statistics, Engineering or other scientific disciplines. Fluent English and strong motivation are required.


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