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LUISS Business School > id corso 4614

immagine: formazione con LUISS Business School

Master in Big Data Management

LUISS Business School

Roma

stage, tirocinio
curriculare

modalità erogazione
formazione in aula

borse di studio, riduzioni
disponibili

facilitazioni
non previste

programmi pubblici
corso non finanziato

termine delle iscrizioni
11 marzo 2019

inizio delle lezioni
25 marzo 2019

durata
12 mesi

costo di partecipazione
14.000 Euro

destinatari
laureati di secondo livello,laureati di primo livello

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Obiettivi

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.

 

Objectives

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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