University Of Padova Masters Data Science. The University of Padova offers a Masters in Data Science that you can complete fully online. For the past 20 years, the University has been working to make its programs accessible to students all over the world. Their goal is to help you develop the skills needed to become an expert in data analysis, which will make you more competitive in today’s job market.

This program consists of two semesters and four courses: Advanced Data Analytics with Python, Data Mining with R and Machine Learning, Big Data Management and Visualization with Tableau, and Business Intelligence with Tableau Server. The first two courses are taught by experts from the university’s faculty members and guest lecturers from both inside and outside Padova. The last two courses are taught by experienced researchers at Padova who worked on real-world projects using Tableau Server.

The program is designed so that students can learn how to use advanced technology while still being able to keep up their professional life. Students are expected to spend around 20 hours per week on coursework throughout each semester, but there are no deadlines or exams during this time frame—you can take breaks whenever necessary!

Big data is one of the key terms to our contemporary world: the existence of nearly limitless amounts of data that need to be collected, managed, analysed and processed by competent professionals, equipped with specific tools. If you wish to train as a data scientist you will receive a multidisciplinary learning path which combines technical skills (with methodologies borrowed from engineering, computer science, statistics and mathematics) with knowledge of different sectors in which data processing is needed. You will therefore be able to processes the data and translate it into information useful for cognitive and decision-making process. You will be able to work in companies that provide IT services, startups and high-tech companies, public administrations and research centers. The course is delivered entirely in English.

University Of Padova Masters Data Science

Curricula
BDMA; Data Science

  Find out more

Characteristics and objectives
The program intends to build Data Scientists whose solid technical background is complemented by a multidisciplinary preparation on various fields in which big data emerge. Highly required by Industries, Consulting Companies and Public Institutions, Data Scientists design and implement the analysis of big data, and provide managers and stakeholders with a clear account of their results. The Graduated in this degree will be able to master tools coming from Engineering, Computer Sciences, Statistics and Mathematics for collecting, managing and analyzing big data, and to translate their work into highly valuable informations.

Occupational opportunities
The Graduates will have jobs opportunity in Italy and abroad in
▪ internet companies, consulting companies;
▪ startups and high tech industries;
▪ public administrations;
▪ research centers.

Curricula
BDMA; Data Science

Teaching list
Training

I Year
OPTIMIZATION FOR DATA SCIENCE [CFU 6]
STATISTICAL LEARNING 1 (MOD. A) [CFU 6]
STATISTICAL LEARNING 2 (MOD. B) [CFU 6]
STATISTICAL LEARNING (C.I.) [CFU 0]
OMICS IN HUMAN DISEASE [CFU 6]
INTRODUCTION TO MOLECULAR BIOLOGY [CFU 6]
SYSTEMS BIOLOGY [CFU 6]
MATHEMATICAL CELL BIOLOGY [CFU 6]
LAW AND DATA [CFU 6]
FINANCIAL MATHEMATICS FOR DATA SCIENCE [CFU 6]
HIGH DIMENSIONAL PROBABILITY FOR DATA SCIENCE [CFU 6]
STOCHASTIC METHODS [CFU 6]
MATHEMATICAL MODELS AND NUMERICAL METHODS FOR BIG DATA [CFU 6]
HUMAN COMPUTER INTERACTION [CFU 6]
PROCESS MINING [CFU 6]
STRUCTURAL BIOINFORMATICS [CFU 6]
KNOWLEDGE AND DATA MINING [CFU 6]
DEEP LEARNING [CFU 6]
MACHINE AND DEEP LEARNING (MOD. A) [CFU 6]
MACHINE AND DEEP LEARNING (MOD. B) [CFU 6]
COGNITION AND COMPUTATION [CFU 6]
FUNDAMENTALS OF INFORMATION SYSTEMS [CFU 12]
GAME THEORY [CFU 6]
NETWORK SCIENCE [CFU 6]
HUMAN DATA ANALYTICS [CFU 6]
BIG DATA COMPUTING [CFU 6]
INFORMATION RETRIEVAL [CFU 6]
MACHINE AND DEEP LEARNING (C.I.) [CFU 0]

II Year
STAGE [CFU 15]
COGNITIVE, BEHAVIORAL AND SOCIAL DATA [CFU 6]
BIOINFORMATICS [CFU 6]
BIOLOGICAL DATA [CFU 6]
LAW AND DATA [CFU 6]
STOCHASTIC METHODS [CFU 6]
TIME-SERIES ANALYSIS FOR BUSINESS ECONOMIC AND FINANCIAL DATA [CFU 6]
BUSINESS ECONOMIC AND FINANCIAL DATA [CFU 6]
STATISTICAL METHODS FOR HIGH DIMENSIONAL DATA [CFU 6]
STATISTICAL LEARNING 1 [CFU 6]
VISION AND COGNITIVE SYSTEMS [CFU 6]
HUMAN DATA ANALYTICS [CFU 6]

University Of Trento Data Science

Introduction

The Master program (Laurea Magistrale) in Data Science will provide graduates with a deep theoretical, methodological, and practical understanding of mathematics and statistics, computer science, while at the same time providing them with domain-specific knowledge in fields like Social and Political Sciences, Psychology, Law, and Business. Graduates will be able to put their expertise to work in the private, public, and third sectors, being knowledgeable about the treatment of data and their analysis. Great emphasis will be given to the acquisition of practical abilities and soft skills – for example, many of the labs and courses will provide teamwork-oriented activities as part of interdisciplinary workshops often with the participation of non-academic stakeholders. These abilities and skills will be further strengthened through training placements within public administrations, private companies, research institutes, and laboratories, as well as stays at other Italian and European universities. The overarching objective of the program is to foster the acquisition of interdisciplinary knowledge applied to concrete cases and of relational, communicative, negotiating, and organizational skills.

 The Master is a multidisciplinary degree offered jointly by the following organizations at the University of Trento:

• Department of Mathematics
• Department of Information Engineering and Computer Science
• Department of Economics and Management
• Department of Psychology and Cognitive Science
• Department of Industrial Engineering
• Department of Sociology and Social Research
• CIMEC – Centre for Mind/Brain Sciences
• and by FBK – Fondazione Bruno Kessler

Objectives 

 The Interdepartmental Master’s Degree Course in Data Science trains students to become data analysis professionals with strong transversal skills and the ability to work in dynamic and multidisciplinary environments with theoretical, methodological, and practical knowledge in computer science, mathematics, and statistics and in one or more of the domains of competence that are at the base of Data Science, such as Social, Cognitive, Economic, Industrial Sciences and Law.

During training, special attention will be paid to the acquisition of know-how and the development of soft skills. As early as the first year the student will be asked to follow a large group of classes that involve laboratory activities, interdisciplinary working groups, and case studies with the direct involvement of experts in the field. These skills are then further developed through internships and traineeships in public institutions, research institutes, laboratories, public and private companies.

The aim is to create a new professional figure capable of combining interdisciplinary knowledge and interpersonal, communicative, and organizational skills, who will be able to hold high-profile technical and/or managerial roles in highly interdisciplinary contexts in the following fields:

• Technology, being able to manage projects and apply innovative solutions in the field of information and IT systems and network technologies, taking into account commercial, socio-organizational and regulatory issues;
• Corporate-organisational, being able to govern complex organizations using modern technologies, such as in the field of e-commerce and web-based services;
• Socio-psycho-economic, being in possession of the basic skills required to design technologically innovative solutions in public and private institutions, such as in the field of eGovernment and market research.

At the end of the course, graduates will be able to work transversally across several departments of a company or administration according to their domains of competence transforming data into actionable information.   By filling the role of Data Scientist in an organization, graduates will be supporting managerial functions with the information required to make informed decisions, sometimes anticipating trends and seizing opportunities of great economic, social, political, or ethical importance as well as in the definition and planning of production, logistical and organizational processes in the private, public and third sector sectors. Depending on their interests, they will also be able to deepen their knowledge of advanced topics in the field of Data Science with applications in specific domains of competence, and/or to explore advanced technical concepts in the fields of mathematics, statistics, and information technology.

Program Overview

The Master’s Degree program in  Data Science is a two-year full-time program taught in English, which aims at training trains professional figures with strong transversal competences that can work in multidisciplinary environments. The person with a master’s degree in Data Science will be able to manage and analyze large amounts of data produced by natural and social systems to support decision-making processes in the economic-productive, political-social, and scientific research activities in the fields of public administration, industry, public and private services, and the third sector.

The person with a Master’s degree in Data Science will be able to hold high-profile technical and/or managerial roles in contexts that require a good combination of skills in computer science, mathematics, statistics, and social, psychological, and economic sciences.

At the end of the course, the person with a master degree in Data Science will be able to analyze the elements that contribute to the formation of the data being analyzed and to identify possible sources of noise, bias, and uncertainty; she/he will be able to use the IT platforms for the storage, management, and transformation of data, being aware of the performance limits and/or the advantages offered by the various platforms; she/he will be able to identify the strategic objectives that can be better-pursued thanks to data analysis, also by effectively combining the methodologies of social and psychological sciences.

The interdepartmental nature of the study course makes it possible to accept students from different backgrounds and to provide them with a highly interdisciplinary curriculum. The first year will include courses aimed at integrating the different competencies and will cover the fundamental disciplines of Informatics, Mathematics, Statistics, and Social, Psychological and Economic Sciences. These introductory courses will be followed by courses and workshops on relevant applications of Data Science, in particular for Social, Psychological, and Economic Sciences. An adequate offer of optional courses and workshops will allow the design of courses aimed at specific areas. As a result,  students earning a master’s degree in Data Science will be provided with a cultural, scientific, and methodological background that will allow her/him to access university programs subsequent to the master’s level (second level Masters and PhDs).

Courses

The Master in Data Science is organized into two curricula. Students can choose one of the two curricula according to their previous studies. 

• Curriculum A is meant for students who have taken a bachelor’s degree (Laurea) in  Computer Science, Mathematics, Physics, Statistics, or Engineering.
• Curriculum B is meant for students who have taken a bachelor’s degree (Laurea) in  Sociology, Economics, or Psychology.

Each curriculum represents a 120CFU workload which includes mandatory courses, elective courses, and labs, open-choice courses, a stage, and a thesis, as detailed below. 

Students in both Curricula should additionally complete the following activities:

• Elective course – II year (6 CFU): Students are required to choose 6 CFU from a list of elective courses that will be advertised in due time (see Regulations for further information).
• Elective laboratories – II year (12 CFU): Students are required to choose 12 CFU from a list of elective laboratories which will be advertised in due time (see Regulations for further information).
• Open-choice courses (12 CFU): Students are required to choose 12 open-choice credits among the courses offered by the University of Trento. The courses listed in the tables above are automatically approved. In all other cases, a personalized study plan must be completed and submitted to the commission for study plan examination.
• Stage (9 CFU). 
• Thesis (18 CFU): The course of studies is concluded with the discussion of an original thesis, under the guidance of a supervisor, providing 18 CFU.

If you’re interested in studying data science at the University of Padova, this guide will help you figure out what it will take to prepare yourself for the program.

The University of Padova offers a master’s degree in Data Science (MDS) that is designed to prepare students for careers in data science and big data analytics. The program covers topics such as machine learning and artificial intelligence, statistical learning and modeling, advanced algorithms, and data mining. Students who successfully complete the program receive an MDS degree from the School of Engineering and Science.

As part of this guide, we’ll talk about:

-What are my options when it comes to studying at the University of Padova?

-What kind of student should enroll in this program?

-Can I apply if I don’t have any previous experience?