|Stato attuale: Da Iniziare|
|Tipologia corso: Master||Livello: 1|
|Posti disponibili:||20||Crediti formativi:|
The Master in Data Science for Management is a first-level international Master program entirely taught in English.
The program offers a comprehensive training in Business analytics from a problem solving perspective, allowing graduates a competitive advantage in a rapidly expanding and highly rewarding job market.
The Master begins in January 2018 and runs until December 2018, on a full-time basis.
Active attendance is mandatory. A minimum of 80% attendance is required.
Classes run from Monday to Friday, 5 hours per day, 9 a.m. - 2 p.m.
Management - 2 ECTS
Statistics - 2 ECTS
Data Management and Warehousing - 4 ECTS
The course illustrates how to implement and technically maintain a data warehouse. The focus is on database data design, extraction, profiling and standardization along with data transformation. A detailed analysis of big data quality management is provided.
Software Development and Technologies for Business Intelligence - 5 ECTS
The course focuses on software development and Object Oriented Programming within the Excel framework. Students will gain broad software development skills to be able to independently write procedures and functions to expand and automate data analysis studies and results.
Statistics and Probability (basics) - 6 ECTS
The aim of this course is to deepen the knowledge of inferential methods for empirical research with applications focusing on economics, management and marketing, both at a univariate and multivariate level. Together with the theoretical concepts, data sets derived from empirical research will be analyzed. The open source software environment for statistical computing and graphics R will be introduced.
Management for Digital Enterprise - 7 ECTS
The course illustrates the business characteristics of a Digital Enterprise along with the impact of a Digital Enterprise on the Customer Experience. At the end of the course students will be able to understand the importance of ensuring that Digital Enterprise initiatives have clear business objectives, and identify the relationships of Digital Enterprise with specific enablers (Digital Marketing, Analytics and Customer Relationship Management).
Geospatial Information Management - 5 ECTS
This course will enable students to develop their Data Science capabilities and learn statistical techniques for managing big spatial data sets. Apart from a theoretical section where the procedures are introduced, a substantial part of the course will be devoted to practical laboratories using the software environment R in which the students will apply the procedures to different real datasets.
Text and Web Mining - 5 ECTS
This course focuses on extracting knowledge from the web by applying classification and clustering techniques on hypertext documents. Students are introduced to information retrieval and filtering methods. Practical applications on web information extraction and text categorization are presented.
Data Mining and Pattern Recognition - 6 ECTS
The purpose of this course is to provide step-by-step instructions for the entire data modeling process, with special emphasis on the business knowledge necessary to successfully use statistical models. Moreover, students will be able to select suitable approaches for pattern recognition, and to compare alternative methods in order to implement the best decision process for the problem under study.
Business Intelligence and Data Analytics - 5 ECTS
This course illustrates the usage of data and analytics in modern business activities. The main focus is on Data Warehousing methodology and Database Marketing set-up in a multidimensional framework. Demand Segmentation and Scoring Models will be the practical applications.
The Master is addressed to graduates with a Bachelor or Master of Science degree, or who expect to graduate by the last session of 2016/2017 a.y., in any of the following fields: Computer Science, Economics, Engineering, Management, Mathematics, Statistics, Physical Sciences.
Alternative degrees may be considered under specific circumstances.
Graduates of this Master program are ideally suited to fill jobs as Big Data Managers across a variety of industries, ranging from ICT to consulting, from banking and finance to insurance. Within companies, Data managers will exploit the ongoing digital revolution delivering analytically-informed solutions to various corporate functions.
The last four months of the Master program are employed to enhance and apply learning outcomes. Students are expected to either: serve an internship, typically with a partner company, and write a thesis related to their activity; or write and defend a project-oriented Master thesis under the supervision of a scholar.
The tuition fee is 9.000 euro to be paid as follows:
- 3.000 euro upon admission;
- 3.000 euro by 31st of May 2018
- 3.000 euro by 31st of July 2018
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