Continuing education

Master's Degree in Sports Big Data and Artificial Intelligence in Sports

Promote sports performance with Big Data in sport and master the most advanced tools to analyse data, optimise workouts and transform sports management.

Alumno del Máster en Big Data Deportivo de UTAMED
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Discover the Master's Degree in Sports Big Data

Fernando Martín-Rivera, director of the master's degree, has more than 20 years of experience in the sports sector. He is a specialist in the analysis of biomechanical signals and statistical data processing. He currently works as a researcher in projects that incorporate AI into the diagnosis of chronic musculoskeletal diseases.

The Master's Degree in Artificial Intelligence in Sports is designed to train professionals to lead the digital era in sports through the intelligent study of data. In addition, you will learn how to build Machine Learning and Deep Learning models, programming languages such as Python, and how to apply AI to optimise processes both in training and in the direction and management of sports teams.

With a study load of 60 ECTS credits, this program is taught 100% online and flexibly, with live classes, access to a virtual classroom with up-to-date materials and continuous monitoring by a teaching team with extensive experience in the sports sector.

Fernando Martín-Rivera, director del Máster en Big Data Deportivo

The master's degree at a glance

  • University-specific degree
  • 60 ECTS credits
  • Duration: 9 months
  • Start: year 26-27
  • 100% online classes
  • Live Masterclass

Discover the teachers of the Master's Degree in AI in Sport

Be trained by a team of experts with backgrounds in large companies and projects applied to Big Data and AI in sport:

Foto de Fernando Martín-Rivera
Fernando Martín-Rivera
Master's Degree Director

Professor and researcher in Sports Sciences and Data Scientist, expert in human movement analysis and application of AI for the diagnosis of musculoskeletal diseases.

Foto de David Sanz
David Sanz
Co-director of the Master's Degree

Vice-Rector of Research at UTAMED. National Award for Arts and Sciences Applied to Sport. Director of the Teaching and Research Department of the Royal Spanish Tennis Federation (2003-2020).

Foto de Rafael Martínez Gallego
Rafael Martínez Gallego

Professor and researcher at the UV, specialist in combining Sports Sciences with Machine Learning and AI in his research. In addition, he is a trainer for the International Tennis Federation.

Foto de Vicente Alepuz Moner
Vicente Alepuz Moner

Telecommunications Engineer from the Polytechnic University of Valencia, head of the Machine Learning and AI department of Colaitec S.L., a company specialised in data analytics.

Foto de Miguel Sánchez Faubel
Miguel Sánchez Faubel

Artificial Intelligence Specialist, graduated in Electronic Engineering from the Polytechnic University of Valencia. He works as a Data Engineer at the company Colaitec S.L.

Foto de Victoria González Gutiérrez
Victoria González Gutiérrez

Telecommunications Engineer from the Polytechnic University of Valencia, expert in databases and implementation of KPIs. She is currently head of quality at the company IonClinics & Deionic.

What are the objectives of this master's degree?

The Master's Degree in Sports Big Data and Artificial Intelligence in Sports will prepare you to apply data analysis and AI in sports contexts, improving performance and decision making. You will develop the following skills:

01

Apply advanced sports analysis methodologies such as Big Data and Machine learning to improve training performance.

02

Know programming languages such as Python and SQL to process, analyse and manage sports data.

03

Develop and optimise KPIs to measure and improve the performance of athletes and the management of sports organisations.

Who is the Master's Degree in Artificial Intelligence in Sports aimed at?

This master's degree is an ideal course for both university graduates and professionals without a university degree who want to expand their knowledge of the analysis of sports data, in order to optimise decision making and training performance. The profiles recommended for the completion of this training are:

  • Graduates in Physical Activity and Sports Sciences.
  • Professionals who want to improve their skills in the field of data analysis applied to the sports sector in terms of performance and sports management. Higher Vocational.
  • Training graduates, especially those who have studied the Sports branch (TSAF) or the Computer Science branch.
  • Managers of sports facilities, sports technicians or any professional related to the areas of technology and sport.
Estudiante del Máster en IA en el Deporte haciendo ejercicio
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Sports Big Data Master's Degree FAQs

What practical applications does Big Data have in sport?

The numerous applications of sports Big Data include data analysis and artificial intelligence in the sports sector, improving performance and strategic decision making. In addition, it allows for the analysis of player, match and training data to optimise strategies and predict results.

How can Big Data improve sports performance?

In the Sports Big Data Master's Degree you will learn to apply advanced analysis methodologies such as Python or Machine Learning to improve training performance and optimise KPIs. Thanks to this knowledge, patterns and trends in the game are identified, allowing coaches to adjust tactics and improve individual and collective performance.

How does artificial intelligence help improve sports performance?

AI in sport helps improve sports performance through intelligent data analysis and process optimisation, which helps with customising workouts, preventing injuries and improving the recovery of athletes, in addition to optimising team management.

How is artificial intelligence changing personalised physical training?

Thanks to artificial intelligence in sports, it is possible to identify patterns and generate personalised training and recovery plans, optimising workloads, preventing injuries and maximising the performance of each athlete in a much more precise way than with traditional methods.