Master in Data Science

Influencing with facts

The Master in Data Science is designed to provide highly specialized training for those who have developed a strong interest in data processing, and would like to hone that skill in terms of searching for facts that can influence the decision-making processes of a company.

By applying some of the most innovative analysis methodologies available and using a wide range of instruments, the course lays the foundation for transforming raw data into operational information that can be used to resolve company problems requiring tactical or strategic decisions.

The course outline overlaps with a range of corporate functions; a linking position, placed within a team of experts responsible for company growth dynamics. With a view to increasing the impact of Data Science processes, the course includes a module dedicated to management communication techniques, which are vital if students are to become representatives capable of dealing with an organization’s senior management.

People who enrol in the Master in Data Science want to learn how to manage a big data business, and are aware of the opportunity that this presents in terms of generating value. Their ability to interpret signals and get results sets them in good stead for a career in medium and large companies or consultancies, realizing their ambition to occupy strategically important roles.

The Master is structured into two terms of classroom-based lessons in English and 600 hours of work experience over a total of 12 months. The training involves a range of skills designed to bring out the three core competency areas: business economics, IT and, lastly, speculative analysis or statistical mathematics. One strength of the Master is that it is not limited to a specific company’s software; instead, participants can experience a range of programming and analysis tools, including open source software.

If you would like to be at the forefront of a key sector for the growth of multinational companies, contact the course Program Manager.

THE MASTER IS AN INVESTMENT.
THE HONOR LOAN IS THE WAY TO FUND IT.

PerTe Prestito Con Lode”, a long-term and low-interest honor loan, with no collateral required to cover the full amount of the tuition fee.

loghi

 

 

In collaboration with:


Claudio Sartori

Claudio Sartori

Director of Studies
claudio.sartori@unibo.it

" With this Master you will learn techniques used to manage, manipulate and analyze increasing amounts of data that trace and nourish the economic and social processes of today. You will also learn how these techniques can be effectively used in businesses for value creation and how the results can be effectively communicated and made available to recipients. "

ACADEMIC YEAR 2015/2016

Academic Background

  • 27 y.o.

    AVERAGE AGE

  • 26%

    FEMALE STUDENTS

Structure

The Master in Data Science is a full-time program structured in 1,500 hours of learning activities over 12 months of study, divided into: 360 hours of lecturing, an estimated 540 hours of independent study, and 600 hours of internship.

The structure of the Master is divided into two terms:

  • First term: November 2018 – February 2019
  • Second term: February 2019 – June 2019
  • Internship: June 2019 – November 2019

The Master offers a series of pre-courses at the start of the academic schedule: Software programming (Python), the foundations of data and SQL, basics in descriptive and inferential statistics, explorative data analysis and the fundamentals of economics.

Classroom participation is about 30 hours per week structured in order to allow time to work in groups, while not neglecting individual students focus and management of interpersonal relationships.

COURSES

At the end of the classroom phase, students experiment with business analytics within a company setting - to support the performance management processes. Phases:

Understand the big picture and design the company's business map
Defining the company's business performance model
Analysis of the results of previous mapping activities
Identifying key questions (KSF) and, as a consequence, the company data needs
Analyzing data availability and sources: internal  (company ICT, Internet of Things, Digital and Social) vs. external data (Social and Digital open data); current vs. potential
Providing information structure and design of analytical methods and tools:
Descriptive (What happened? What’s happening?)
Exploratory (Why did this happen? Why is this happening?)
Predictive (What will happen?)
Prescriptive (How to optimize?)
Supporting the company  in the analysis of results and in the definitions of its business plan



The digital revolution has led to an explosion in the amount of available data and information (Big Data), the ability to analyze and correlate this information is becoming a fundamental element to an enterprise’s competitiveness and a new source of economic value and innovation. Big Data, however, is unable to be managed properly by using traditional instruments of Information Technologies because of their size, their heterogeneity and their many peculiarities. For this reason, new architectures, methodologies and tools are being created for data scientists to transform this data into value for the company and to support the decision-making process. This course will analyze the various types of data available, technical access to information, methods to handle them and the architectures and tools to store and process them.



Business intelligence (BI), motivations, objectives, definitions and solutions. Data warehousing as an enabling technology for BI: architectures, techniques and methodologies of On-Line Analytical Processing (OLAP) for data analysis. Multidimensional modeling with the Dimensional Fact Model (DFM). Self-service BI platforms. Relational OLAP. What-if analysis. Laboratory exercises on OLAP, DFM and self-service BI.



The new priorities of marketing management: the marketing metrics and dashboard indicators of marketing.  From the value for the customer to the value of the customer: customer value, satisfaction, loyalty and customer equity. Analysis, measurement and management. Customer Relationship Management: acting on acquisition, retention and development. Big Data and Customer Insight Management. Customer insights and Big Data for improving marketing decisions and management. Marketing Modeling and Marketing Analytics.



Models and methods for knowledge extraction from databases. Study of different types of data and methods of pre-treatment. The functions of Data Mining. Supervised and unsupervised learning. Algorithms and methods for constructing classification models. Clustering algorithms. Algorithms for discovering association rules. Methods for evaluating the quality of data mining results. Data mining laboratory in order to apply the studied methods.

 



Modern manufacturing processes exploit massively the digital technology, as is witnessed by the increasing interest towards the new operating paradigms known as “Industry 4.0”. The purpose of this module is to exploit the skills acquired in other modules, mainly “Data analysis”, “Data Mining” and “Operation Analytics”, to deal with the “Manufacturing data” and to extract information useful for increasing the effectiveness of manufacturing.



The purpose of the course in Digital Analytics is to provide the most widespread analysis methods used in the field of web marketing. The course will explain analytics, starting from the definition of the objectives and KPI onto advanced report and data visualization. It will also include a strong technical and informatic component through which it will be possible to implement various analytics strategies. Google Tag Manager and Google Analytics will be the main instruments available.



Processes of Data Science are considered here in terms of their communicative value, or rather within the theories of communication, on the one hand, and strategies of business communication, on the other. These insights will be able to propose and critically interpret the socio-communicative context in which the potential of data science is developed. These conceptual aspects will be demonstrated during the analysis of specific cases making the communicative and human aspects fully explicit.

 



This course provides a brief introduction to machine learning for statistical pattern recognition. Topics include: a background on decision and supervised learning theory, classic generative and discriminative models, support vector machines, neural networks, ensemble methods and model selection practices. The course also puts emphasis on the application of these models and techniques to practical problems drawing on (Python) code examples and exercises.



This course provides students with a deep understanding of the following topics: the reference model. The analytics for understanding the pattern and the business dynamics of an enterprise. Business process analytics, market, custodian and supply chain analytics; analytics of competitors. Financial cost and revenues analytics. The use of business analytics in the design of systems for measuring the company's performance.



Nowadays, knowing the opinion of the media about your enterprise or a certain topic represents an important competitive edge.
The module introduces techniques, methodologies and software used in these kinds of projects. The main topics covered are:

  • Introduction to the systems of Social Media Monitoring and Social Business Intelligence
  • Architectures, techniques and methodologies for the systems of Social Business Intelligence
  • Social networks
  • Social Media Monitoring: laboratory with Brandwatch


This course explores the following topics; Univariate analysis: Distributions of quantitative and qualitative traits. Summary indicators: average values and variability indices. Data transformations. Graphical representations. Association between variables: Connection, covariance, correlation. The linear regression model. Elements of probability calculation: Probability (Binomial, Poisson, Normal). Signals of statistical inference: confidence intervals and hypothesis testing. Analysis of multidimensional data: Matrices of data, variance and covariance, correlation and dissimilarity. Laboratory exercises with dedicated software.



The course will explore and analyze typical problems associated with operations management and address them through quantitative modeling in support of decision making. The issues will be handled by combining a business-oriented approach with quantitative methods on a statistical and econometric basis. The main contents are related to: management of production capacity, inventory management and control, service operations, selection and monitoring of suppliers, process optimization and simulation. The main objectives of the course relate to the ability to model complex business situations and to analyze them through technical and quantitative tools designed to monitor and improve business performance, teams and individuals.



The laboratory work plan addresses the complete process of data analysis, starting with loading data using different approaches and the development of models for analyzing and visualizing the results. It will cover low-level technologies such as Hadoop / MapReduce and Spark (computing framework for performing analysis functions on distributed data or residing in main memory) via programming languages (Python), and platforms / tools at the higher level such as: IBM Big Insights, which mediates the complexity of Hadoop and enriches data analysis tools; Pentaho ETL and BI as a system that integrates with Hadoop; Tableau for displaying results.

___________________________________________________________________________________________________________________________________________________________________________________________

Corso tenuto dallo staff CINECA (Dipartimento Super Calcolo, Applicazioni e Innovazione
e Laboratorio Big Data e Analytics), coordinamento di Stefano Roselli



Learning method

The educational sessions provide different learning methods, including lectures, simulations, discussions of case studies and presentations by companies, testimonials, and group work.
The curriculum is completed with master lectures held by professionals from the worlds of business, academia and politics, with opportunities for discussion and interaction with the business world through case histories.

CAREER DEVELOPMENT

The integration with companies is a priority and an ever-present feature of all programs of the Bologna Business School, hence for the Master in Data Science too.
The School is fully committed to creating employability, by way of a systematic career service action, constantly focused on matching at best the students’ professional projects with the needs companies have.
The internship is an exceptional springboard, suffice it to say that six months after the end of the full-time masters at Bologna Business School on average 90% of students work in a company.
The BBS Career Service assists and supports students since the very beginning, along a training and professional development path. This is accomplished by organizing a series of workshops, with the aim of providing the fundamental tools and resources to be appropriately prepared for the labor market.

 

To achieve this goal, students are involved in several workshops, among which we may list:

  • Writing a CV and a Cover Letter
  • How to create an effective Linkedin profile
  • How to prepare for a job interview
  • The labor market in Italy

 

In addition to this, thanks to the collaboration with professional career counselors, students receive a customized service, in order to understand their strengths and to build a professional development plan, which will turn out to be helpful when looking for an internship. Here follow some of the activities:

  • Initial guidance interviews
  • Specific interviews, focused on one’s own career plan
  • Mock interviews
  • Continuous support to students with one – to – one sessions

 

Finally, all students can use Job Teaser, a career platform allowing them to be constantly updated on events and job postings in our partners companies, and much more.

Alumni

Peter Engerer – Germany

Data Scientist, Engineering Ingegneria Informatica
Data Science (A.Y. 2016/2017)

"As an academic researcher, I was looking for a short program that would allow me to enter the world of Data Science. Having experienced the beauty of Bologna, knowing the reputation of the Alma Mater, combined with the strong partners made me choose the Data Science Master at BBS. Thanks to the school’s business network, I am currently working as a Data Scientist for one of the Italy’s largest IT companies."

Luca Tagliati – Italy

Business Analytics Specialist, Iconsulting
Data Science (A.Y. 2016/2017)

"Thanks to the Master in Data Science I improved my education in a sector which is growing and requires expertise in IT, Economy and Statistics. It has also been an opportunity to grow personally thanks to Italian and international colleagues, with whom I shared challenges and debates. I think that them the Faculty, the Staff and the Network of BBS, represent the real value of the experience I have lived."

Sameer Rohadia – India

Content Manager (Training & Community), Continental AG
Data Science (A.Y. 2016/2017)

"After 17 years of industry and teaching experience in India, I approached the field of Data Science and I discovered the Master of BBS. The international dimension, helped me to interact with colleagues from different countries. Currently, I prepare contents and provide training programs in the area of Big Data and Advanced Analytics in Continental AG (Germany).BBS will always be close to my heart."

Daniele Frassineti – Italy

Data Scientist, Intesa San Paolo
Data Science (A.Y. 2015/2016)

"Today world is dynamic, old certainties are questioned and new opportunities are created. The Master in Data Science was the chance to catch these opportunities, opening up the doors for an extremely stimulant world. It allowed me to approach companies at the cutting edge of innovation. In Accenture, I started my career, and now I work at Big Data Lab of Intesa San Paolo, thanks to the knowledge gained at BBS."

Lorenzo Cellini – Italy

Business Analytics Expert, Iconsulting
Data Science (A.Y. 2015/2016)

"The Master in Data Science provides you with skills and a mindset that are essential if you aspire to become a Data Scientist. The faculty is composed by numerous experts of the sector, capable of providing you with their academic knowledge and above all, with practical experiences directly coming from the professional world. These aspects make the experience unique and extremely interesting."

Elena Cipressi – Italy

Research Fellow, Empirix
Data Science (A.Y. 2015/2016)

"This is an educational path which connects people, expands knowledge and improves your academic background; there are countless sources from which you can deduce the role of Data Scientist. This Master adds one more dimension: the human one, by giving everybody the opportunity to customize it with critical thought, thanks to the continuous interaction between students, professors and professionals."

COMPANIES

The goal of the Career Service is also to allow students to connect with national and international companies. Over the years, Bologna Business School has managed to establish a wide-ranging network and a sound partnership with leading companies in Italy, thanks to a personalized approach, based on each company’s needs. The collaboration features the following activities:

  • Sending the CV book
  • Sharing internship and work opportunities
  • Presentations at the School premises
  • Career Day
  • Implementation of project works
  • Class-room activities with case studies presented by managers and/or HR professionals

 

If you need more information regarding the composition of the class such as age, geographic origin and students’ background, you can download the class profile, clicking here: class profile_DataScience

 

Our partners are the foremost supporters of our students, with the provision of scholarships, internships and professional opportunities.

Bologna Business School’s partner companies for the Master in Data Science are:

ACCENTURE AMAZON ANALYTICS NETWORK BARILLA BHALSEN BIRRA PERONI BLUE 449 BTO BUCCI INDUSTRIES CAMST CAREGIVING CARPIGIANI CHAMPION EUROPE CINECA CLARINS CLUB MED CON.TE COOP ALLEANZA 3.0 COSTA CROCIERE DATALOGIC DAVINES DEDAGROUP DELOITTE DIENNEA DOVE CONVIENE - SHOPFULLY DUCATI EATALY EGS SOLUTION ELECTROLUX ENEL ENGINEERING GENERALI ASSICURAZIONI GLAM GOOGLE GROUP M H&M HERA IBM ICONSULTING IMA IREN KPMG LAMBORGHINI LIU JO MAX MARA MONTENEGRO NESTLE' NIKE NOMISMA PRADA PUBLICIS MEDIA PWC SACMI SCS CONSULTING SYSDATA TECHNOGYM TETRAPAK UNIGRA' VALSOIA VODAFONE WEBRANKINGYOOX NET-A-PORTER GROUP

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FEES

The tuition fee for the Master is 14,800 euros (VAT free) to be paid in three installments:

  • First installment: 1.850,00 euros
  • Second installment: 7.000,00 euros
  • Third installment: 5.950,00 euros

The fee includes participation in the Master, all the study material available through the online platform, and access to the services and facilities of  Bologna Business School such as: personal account for the BBS wi-fi, use of the PCs in the Computer Lab, access to the study areas, access to the internal gym, special rates for the School restaurant.
Furthermore, the fee gives participants the right to take advantage of the supporting activities of the School, such as the language courses and the master lectures by invitation. Free parking is also available within the BBS campus.

Additionally, with the Student Card of the University of Bologna, students have access to all of the university facilities, including over 100 libraries, digital resources and study halls (including databases and online subscriptions); the three city center canteens and all university student related discount offers. More information is available on the site of the University of Bologna: http://www.unibo.it/it/servizi-e-opportunita

HONOR LOAN

Thanks to the agreement between Bologna Business School and Intesa Sanpaolo, participants are eligible to apply for “PerTe Prestito Con Lode“, a long-term and low-interest honor loan.

Main characteristics:

  • Loan amount equal to the enrollment fee
  • Reduced interest rate
  • No collateral required
  • Repayable in 10 years
  • No early closing fees

 

Download the description document here.

SCHOLARSHIPS

At Bologna Business School we understand the importance of financial aid in supporting our students to achieve their educational goals. We are aware that an advanced, high quality training path can be a significant commitment but we also truly believe that investing in one’s future always pays back.

Bologna Business School is pleased to offer partial scholarships to the most meriting students. All of these scholarships are merit-based and will be awarded to the top-ranked candidates in the selection process. The students who come out on top in the selections will be students who not only come from strong academic or practical backgrounds but also those who display the strongest motivation to take part in this program.

There are scholarships of 6,000 euros and scholarships of 4,000 euros. All applicants will be considered for a scholarship – no specific application is required. The scholarships are awarded over the course of every round of selection and if you have performed well enough to merit one of them, you will be informed at the moment of admission.

The scholarships act as tuition waivers, so that they result in a deduction of the total amount of the tuition fees due.

REQUIREMENTS

For the registration it is necessary:

  • a Bachelor’s Degree (must be obtained by the enrollment deadline)
  • English language proficiency

Admission to the program is subject to the positive assessment of your individual interview and English test, if it’s not the candidate’s native language.

APPLICATION PROCESS

This Master’s is open to all applicants with a bachelor’s degree obtained before the enrolment deadline of each round.
There are two rounds of admissions, the first round will be open for applications until July 3, 2018.
 The second round will open on July 4, 2018 and will close on October 3, 2018.

Application steps:

Documents to send to datascience@bbs.unibo.it:

  • CV
  • Degree certificate with accompanying transcript
  • Photocopy of you ID or passport
  • Motivation letter
  • Reference letter(s) (optional but advised)
  • Signed copies of your enrolment summary sheet and receipt for the application fee (both downloadable from ‘studenti online’ following registration)

The selection process will be held at  Bologna Business School. The selections for the first round will take place on July 10, 2018
 and the selections for the second round will take place on October 9, 2018.
In line with the number of available places, admission to the program is granted according to the position on the list of qualified candidates, drawn up on the basis of the total score awarded at the end of the admissions process.

Detailed information on the requirements and application process are available in the “Official Call for Applications” downloadable below.

FAQs

Of course we will. Non-EU citizens have to apply for a student visa before being able to commence their studies. We can provide you with a letter of admission as well as a letter of support, which you can use to make your visa application. In the case of particular problems our staff will be ready to contact embassies directly to discover the source of the problem and solutions to fix it.
After you arrive in Italy, you will be required to apply for a residence permit. Our staff will be able to help you fill out the forms and give you any support you need for this process as well.
If you do not live in Italy then you can participate via Skype. You will be contacted several days before the selection date to inform you of your time slot for the test and individual interview. At this point you can send us your Skype ID so that we can add you to the account that will be used for the interviews.
Yes. Don’t worry if you if you are unable to present a IELTS or TOEFL, your level of English will be assessed during the selection process. You can be excused from the need to present proof of your English level if you are a native English speaker.
The second level Master is accessible only to those who have a bachelor's degree from the old system or a Laurea Magistrale/Specialistica. To access the first level Master a three-year undergraduate degree or a bachelor’s degree in the old system is sufficient.
Access to a first level University Master requires at least a three-year Bachelor’s degree (or the Bachelor’s degree in the old system); for a second level Master's Degree, the Laurea Magistrale/Specialistica (or the Bachelor’s degree of the old system) is necessary.
Enrolling in multiple university courses is not allowed. Therefore, if you are already enrolled in a degree at this or another university prior to registration into the master you are required to apply for a suspension of studies ("career freeze") at the secretariat of the specific School. During the suspension period you will not be able to undertake exams nor accumulate attendance related to the suspended degree.
Upon registration and payment of the admission fee, you must submit or send via registered mail to Alma Bologna Business School (Via degli Scalini 18-40136 Bologna), the following documents:
• a copy of the receipt for the fee of 60.00 euro for administrative services;
• summary sheet;
• a copy of your ID;
• Undergraduate Degree (or substitute statement);
• curriculum vitae;
• any additional titles to be assessed for admission purposes.
No, once you pass the selections, you can decide whether to formalize the registration to the Master through the registration process. However, it is essential to participate in the selection process and to pass it in order to be able to register.
It is essential, for the purpose of registration, to have completed the degree by the registration deadline.
As long as you have passed the selection process, you can still register as an auditor.
An auditor is someone who participates in a master and who has passed the selection stage but doesn’t have an MA/Specialist degree/degree according the old system/ or hasn’t be graduated within the call’s deadline. An auditor can participate in all lessons, academic activities and to the internship (not compulsory). An auditor doesn’t need to take exams and therefore is not awarded CFU. An auditor will however receive a certificate of attendance by the University of Bologna. Instead of paying €11.200 an auditor pays €9.200
You can contact the Help Desk directly via e-mail: help.studentionline@unibo.it, or by telephone: +39 0512099882; or you can apply online: https://studenti.unibo.it/sol/welcome.htm
The School supports students in finding housing, providing references of accommodation facilities and private residences that have been used by former students.
The School organizes several occasions for meetings, discussion, networking, training, refresher training reserved for the Alumni Community (those who have attended a course in Alma Bologna Business School). For further information visit the Community section of our website.
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