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Start   >  Master's & postgraduate courses  >  Education  >  Postgraduate course in Sports Analytics
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  • discount
    10% discount if you enrol before 15th December

Programme

Edition
1st Edition
Credits
15 ECTS (120 teaching hours)
Delivery
Face-to-face
Language of instruction
Spanish
Fee
€4,500 €4,050(10% discount if you enrol before 15th December)
Payment of enrolment fee options

The enrolment fee can be paid:
- In a single payment to be paid within the deadline specified in the letter of admission to the programme.
- In two instalments:

  • 60% of the amount payable, to be paid within the deadline specified in the letter of admission to the programme.
  • Remaining 40% to be paid up to 60 days at the latest after the starting date of the programme.
Notes 0,7% campaign

Registration open until the beginning of the course or until end of vacancies.
Start date
Classes start: 11/02/2021
Classes end: 15/07/2021
Programme ends : 09/09/2021
Timetable
Tuesday: 6:00 pm to 9:00 pm
Thursday: 6:00 pm to 9:00 pm
Taught at
Tech Talent Center
C/ de Badajoz, 73-77
Barcelona
Why this programme?
The importance of data in today's society is beyond any doubt, not only in fields strictly related to business, but also in the world of professional sport. Sports associations and institutions and private companies in the sector have a large amount of data, which require mechanisms for collection, storage and analysis to obtain the valuable information that an organisation needs.

Data management and analysis enables a differential value based on this information to be extracted, managed and generated. Today, sports analytics is a new area experiencing constant growth, and is fundamental for decision-making and team management.

The postgraduate course in Sports Analytics provides a unique opportunity to combine advanced data analysis and passion for sport. The training is carried out in partnership with Futbol Club Barcelona, one of world's leading clubs and a pioneer in data analysis in sport. This partnership means students can work with top-level data, event data and tracking data, and on solving applied problems. In addition, students will be able to obtain a real and privileged view of the application of sports analytics in a leading club in the field.

The postgraduate course provides a comprehensive and broad-based perspective of a data ecosystem applied to the sports field, with an in-depth look at data management and data analytics. The training provides an overview of all the components and tasks currently involved in the application of sports analytics.

After completing the postgraduate course, participants will be able to work professionally in football clubs and in other sports or in private companies, as well as in the field of consultancy and research for sports associations and companies.

Aims
  • Understand the paradigm of open data and be aware of the problems of data management and analysis in sports.
  • Practice using the main data management and analysis tools that are currently being applied to sport data analysis (event data and tracking data).
  • Identify the statistical or machine learning models that are most suitable for a given problem.
  • Be able to perform pre-processing of data.
  • Be able to evaluate the success rate of the proposed models.
  • Obtain specific knowledge about data management and analysis for decision-making.
Who is it for?
  • Graduates in computer science or equivalent qualifications, statistics, mathematics, physics or engineering.
  • Computer professionals, primarily developers, architects, data analysts and systems administrators, interested in data management and analytics applied to the sports sector.
Those interested must have technical training in centralised databases, programming and statistics.

Training Content

List of subjects
3 ECTS 24h
Sport Analytics
  • Introduction to sports analytics.
  • Introduction to game analysis.
  • Football methodology. Barça DNA.
  • Sports analytics in other sports.
  • Advanced data analysis in football.
  • Physical performance data.
  • Artificial intelligence applied to basketball.
4.5 ECTS 36h
Data Management
  • Introduction: big data, cloud computing and services engineering (XaaS).
  • Data management on cloud databases (NoSQL).
  • Distributed data processing and analysis.
  • The most commonly used unstructured and semi-structured data models.
  • Streams management.
  • Geospatial and trajectory data management.
  • Data integration and quality.
  • Visualisation.
4.5 ECTS 36h
Data Analysis
  • Introduction: basic statistics.
  • Statistical inference, sampling and validation of the method.
  • Statistical modelling and calibration of models.
  • Knowledge discovery in databases.
  • Principal component analysis.
  • Clustering methods.
  • Decision trees.
  • Classification methods: discriminant analysis y Support Vector Machine (SVM).
  • Neuronal networks.
  • Convolutional neural networks.
3 ECTS 24h
Final Project
The objective of this module is to put into practice the concepts explained in the 3 previous modules based on a case of use.
Degree
Postgraduate diplomas issued by the Universitat Politècnica de Catalunya. Issued pursuant to art. 34.1 of Organic Law 4/2007 of 12 April, amending Organic Law 6/2001 of 21 December, concerning Universities. To obtain this degree it is necessary to have an official. Otherwise, the Fundació Politècnica de Catalunya will only award them a a certificate of completion.

Learning methodology

The teaching methodology of the programme facilitates the student's learning and the achievement of the necessary competences.

Learning tools
Participatory lectures
A presentation of the conceptual foundations of the content to be taught, promoting interaction with the students to guide them in their learning of the different contents and the development of the established competences.
Solving exercises
Solutions are worked on by practising routines, applying formulas and algorithms, and procedures are followed for transforming the available information and interpreting the results.
Case studies
Real or hypothetical situations are presented in which the students, in a completely participatory and practical way, examine the situation, consider the various hypotheses and share their own conclusions.
Tutorship
Students are given technical support in the preparation of the final project, according to their specialisation and the subject matter of the project.
Assessment criteria
Attendance
At least 80% attendance of teaching hours is required.
Level of participation
The student's active contribution to the various activities offered by the teaching team is assessed.
Solving exercises, questionnaires or exams
Individual tests aimed at assessing the degree of learning and the acquisition of competences.
Completion and presentation of the final project
Individual or group projects in which the contents taught in the programme are applied. The project can be based on real cases and include the identification of a problem, the design of the solution, its implementation or a business plan. The project will be presented and defended in public.
Work placements & employment service
Students can access job offers in their field of specialisation on the My_Tech_Space virtual campus. Applications made from this site will be treated confidentially. Hundreds of offers of the UPC School of Professional & Executive Development employment service appear annually. The offers range from formal contracts to work placement agreements.
Virtual campus
The students on this postgraduate course will have access to the My_ Tech_Space virtual campus - an effective platform for work and communication between the course's students, lecturers, directors and coordinators. My_Tech_Space provides the documentation for each training session before it starts, and enables students to work as a team, consult lecturers, check notes, etc.

Teaching team

Academic management
  • Abelló Gamazo, Alberto
    View profile in futur.upc / View profile in Linkedin
    Associate professor at Universitat Politècnica de Catalunya (UPC), where he obtained his PhD in 2002 and has been working as a lecturer and researcher. His areas of expertise are Databases, Data Warehousing and Big Data Management. He coordinated at UPC European Erasmus Mundus programmes, both master and PhD, and a Marie-Curie ITN, as well as H2020 projects and R&D agreements with Hewlett Packard, Zurich Insurance, SAP or the World Health Organization. He has successfully advised 8 PhD thesis, publishing more than 30 journal and 75 conference articles, as well as more than 10 book chapters (H-index 28 Google Scholar).
  • Romero Moral, Óscar
    View profile in futur.upc
    Doctor in Informatics from the UPC. Lecturer in the Department of Service and Information System Engineering at the UPC. Teaching at both undergraduate and official master's degree level. UPC coordinator of the Erasmus Mundus Master's Degree in Big Data Management and Analytics (BDMA) and in the specialization Data Science of Master in Information Research and Innovation (MIRI-DS). Researcher in the field of data and information management, in which he has published more than 50 publications in conferences and international journals. He has worked as a consultant with SAP, HP and the WHO, among others.
Teaching staff
  • Aluja Banet, Tomàs
    View profile in futur.upc
    Lecturer in the Department of Statistics and Operations Research at Universitat Politècnica de Catalunya (UPC). He has authored more than 50 articles published in scientific journals and studies. He has worked as a statistical consultant for La Caixa, TNS-Sofres AM, the Statistical Institute of Catalonia, and Barcelona City Council, among others.
  • Vázquez Alcocer, Pere-Pau
    View profile in futur.upc
    PhD in software from the Universitat Politècnica de Catalunya (UPC). Professor at the UPC, he, currently, teaches undergraduate and master courses at UPC. He has previous experience teaching undergraduate and master courses in other universities such as the University of Nuremberg, the University of Girona, the Universitat Oberta de Catalunya, or the University of Vic.

Associates entities

Strategic partners
  • Barça Innovation Hub
    • Participates in the design of the contents of the programme, and ensures they are appropriate to the needs of the professional sphere.
    • Disseminates the programme in the professional sphere and area of expertise.
    • Provides teachers and lecturers.
  • Fútbol Club Barcelona
    • Participates in the design of the contents of the programme, and ensures they are appropriate to the needs of the professional sphere.
    • Disseminates the programme in the professional sphere and area of expertise.

Career opportunities

  • Sports analytics consultant.
  • Sports data analyst consultant.
  • Sports data scientist.
  • Sports data engineer.
  • Sports data architect. 
  • Digital transformation leader.
  • Decisional systems engineer.

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  • If you have any doubts about the postgraduate course.
  • If you want to start the registration procedure.
How to start admission
To start the enrolment process for this programme you must complete and send the form that you will find at the bottom of these lines.

Next you will receive a welcome email detailing the three steps necessary to formalize the enrolment procedure:

1. Complete and confirm your personal details.

2. Validate your curriculum vitae and attach any additional required documentation, whenever this is necessary for admission.

3. Pay €110 in concept of the registration fee for the programme. This fee will be discounted from the total enrolment fee and will only be returned when a student isn't admitted on a programme.

Once the fee has been paid and we have all your documentation, we will assess your candidacy and, if you are admitted on the course, we will send you a letter of acceptance. This document will provide you with all the necessary information to formalize the enrolment process for the programme.




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