CURRICULUM

The Master in Big Data Management is a 12-months program of intensive training, designed to develop the unique skill set required for a successful career in the world of big data and business analytics. After the Induction Week, the Term 1 provides strong economic and analytical fundamentals, covering data management and statistics and providing an overview of the cutting-edge tools and techniques related to big data.  During the Term  2 and 3, students experience the core business courses to build professional and personal competences. The Term 4 is dedicated to the Field Project during which students put their knowledge into practice.

Each term is described in detail below:

 

Preparatory Courses

  • Data Management for Big Data Introduction
    Overview of clustering computer frameworks: Hadoop & Spark.
  • Economics of Strategy
    Analytical toolkit and conceptual frameworks of economic science required for understanding and interpreting the economic world, making rational choices and defining successful business strategies.
  • Introduction to Big Data Infrastructure
    Basic concepts of data warehousing and the evolution of these concepts in an architecture for Big Data. Developers learn to write SQL queries against single and multiple tables, manipulate data in tables and create database objects. 
  • Introduction to Big Data Programming
    Practical introduction to data management and programming with R.
  • Introduction to Statistics for Data Scientists
    Basics of Statistics necessary to be a Data Scientist.

Core Courses

  • Accounting
    Introduction to the basic concepts and standards underlying financial accounting systems. Focus on the construction and interpretation of basic financial accounting statements.
  • Business Law
    Introduction to ethical and legal notions of privacy, anonymity, transparency and discrimination, in reference to the Community regulatory framework and its evolution in progress.
  • Financial Management
    Introduction to financial management, including historical behavior of financial time-series, time-value of money, portfolio optimization and measures of risk.
  • Organization & Human Resource Management
    Introduction to Industrial Organization, including pricing models, supply and demand models and network analysis.  While the course covers the theoretical part of such models, the focus is primarily empirical.
  • Strategy
    Skills and techniques in business strategy formulation and the strategic management of organizations.
  • Access Tools and Informational Discovery
    Understand the main concepts of Text Analysis and handle the techniques of Natural Language Processing (NLP). Particular attention on explaining the methods to extract relevant information from data, using Topic Detection and Modeling techniques.
  • Advanced Programming
    Advanced techniques of programming with R, including package development and reporting in markdown.
  • Advanced Visualizations
    Foundations for understanding current state of the art in data visualization. Enables use of advanced data exploration and visualization tools (R and Tableau) to create their front-end to business users.
  • Economic Forecasting
    Introduction to the practice of forecasting economic time series, including theoretical methodologies followed by an extensive application in R.
  • Econometrics
    Introduction to econometrics, including theoretical methodologies followed by an extensive application in R.
  • Machine Learning
    Introduction to machine learning, including both supervised and unsupervised learning algorithms.
  • Marketing Analytics
    Identify and understand digital marketing metrics to measure the success of both social media and traditional web marketing initiatives and campaigns.

FIELD PROJECT

The Field Project is the last mandatory part of the program which represents a great opportunity for students to apply the knowledge and competences acquired during the Master’s program. Each type of filed project helps students to accelerate their career advancement. Students will combine theory and practice, build professional connections, gain relevant work experience, strengthen their creative and analytical skills and increase their future employability.

The Field Project can be one of the following:

  • Internship: From educational training to the job reality. Students participate in an internship that will follow the educational program. Each Master’s program offers various internship options with different requirements to work in companies and organizations.
  • Entrepreneurial Project: Students develop their own business idea: from idea creation to the business plan and go-to-market.
  • Research Project: Students develop a research-based project on a subject identified together with the Faculty.