Big Data and Management - Major of the Master in Digital and Business Transformation Luiss Business School

LUISS Business School’s Master in Big Data Management, provides young professionals with the skills to be at the forefront of modern Business Analytics technique and to become accomplished Data Scientist.

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The Master in Big Data and Management program at Luiss Business School prepares students to work effectively with complex, large-scale, real-world data and to create business value from it.
It focuses on improving the understanding of customer patterns to increase business and improve profitability.  Working in big data management requires a highly interdisciplinary set of competencies: a deep practical expertise in programming and computer science, a good working 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 curriculum of the Master in Big Data and Management 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 a business analyst. Today many companies, including large industries, consulting firms, and marketing specialists are currently on the hunt for these types of professionals.

Aims

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
  • Capability to understand, visualize, and communicate findings to the top management
  • Ability to create data-driven solutions that boost profits, reduce costs, and improve efficiency

 Learning methods and key courses

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

Objectives

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

General management

General management courses aim to give all students the necessary business management foundations in order to better understand new concepts that will be introduced during the core and advanced courses. The general management courses provide students with an overview is highly useful upon entering the job market.

  • Strategy
  • Accounting
  • Organisation & HR Management
  • Business Law
  • Economics of Strategy

Core courses

The core courses introduce students to industry-focused concepts that are specific to this major. These courses provide students with the key principles and skills they need to better understand their chosen sector.

  • Data Science Toolkit
  • Programming for Data Analysis 1
  • Statistics for Data Science
  • Econometrics
  • Python for Finance
  • Big Data Programming Models
  • Programming for Data Analysis II

  • International class
  • Lessons in foreign language 100%
Criteria for assessing applications:
  • CV Screening
  • Language test and/or interview
  • Logical, psychological and behavioral tests
  • Motivational interview
Admission Requirements:
  • Bachelor
Contribution to selections: YES
Luiss Business School offers deserving candidates up to 3 partial scholarships (covering up to 25% of the tuition fee). The scholarships will be granted based on merit. All candidates will be considered for this award.
Cost of the master: Not declared
Scholarships available
  • Shuttle service
  • Tutoring
  • Laboratories
  • Wifi access
  • Disability services
  • Canteen/Meal tickets
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Luiss Business School

        Big Data and Management - Major of the Master in Digital and Business Transformation

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                    • Other editions
                    • Rome - Italy September 18, 2023

                    Social stream

                    Provenance Students Worldwide:
                    Detail of origin:
                    Europe
                    25%
                    45%
                    30%
                    %
                    %
                    Italy
                    20%
                    30%
                    50%
                    %
                    %
                    Gender:
                    50%
                    50%
                    Age of participants:
                    • Under 25

                      25%
                    • 26 - 30

                      50%
                    • 31 - 35

                      25%
                    Foreigners:
                    45%
                    Profession Teaching Staff:
                    50%
                    University professors
                    40%
                    Managers
                    10%
                    Entrepreneurs
                    * The data could be related to the School and not to the Master