SCHOOL OF COMPUTER SYSTEMS ENGINEERING
Master in Big Data Projects
Specialize in big data project management and master the handling of large volumes of data in real-world environments.
SCHOOL OF COMPUTER SYSTEMS ENGINEERING
Master in Big Data Projects
Specialize in big data project management and master the handling of large volumes of data in real-tworld environments.
Start date
September 2026
Pre-registration
March 2026
Credits
60 ECTS
Places available
32
Language
Spanish
Duration
9 months
Format
Online
Schedule
Fri-Sat
Presentation
The Master in Big Data Projects is a proprietary degree awarded by the Universidad Politécnica de Madrid that prepares professionals to manage data projects end to end, combining technical foundations, data analysis, machine learning, and big data technologies applied to real business environments.
Start date
September 2026
Pre-registration
March 2026
Credits
60 ECTS
Places available
32
Language
Spanish
Duration
9 months
Format
Online
Schedule
Fri-Sat
Presentation
The Master in Big Data Projects is a proprietary degree awarded by the Universidad Politécnica de Madrid that prepares professionals to manage data projects end to end, combining technical foundations, data analysis, machine learning, and big data technologies applied to real business environments.
What will you learn?
Comprehensive training in big data projects. The program is designed to prepare professionals to manage big data projects through a progressive learning path structured into four modules:
01.
Artificial Intelligence
Foundations of Mathematics, Programming, and Artificial Intelligence
02.
Big Data
Management and analysis of large volumes of data
03.
Deep learning
Machine learning and deep learning
04.
Lab
Big data technologies applied through laboratories and seminars
Upon completion of the master’s program, students will have a comprehensive and practical understanding of big data projects, from fundamental concepts to the most advanced solutions currently used in the market.
Technologies included in the program


















What will you learn?
Comprehensive training in big data projects. The program is designed to prepare professionals to manage big data projects through a progressive learning path structured into four modules:
01.
Artificial Intelligence
Foundations of Mathematics, Programming, and Artificial Intelligence
02.
Big Data
Management and analysis of large volumes of data
03.
Deep learning
Machine learning and deep learning
04.
Lab
Big data technologies applied through laboratories and seminars
Upon completion of the master’s program, students will have a comprehensive and practical understanding of big data projects, from fundamental concepts to the most advanced solutions currently used in the market.
Technologies included in the program

















Who it’s for?
The Master’s in Big Data Projects is aimed at both professionals who wish to specialize in the field of data and companies interested in enhancing their teams’ skills in big data technologies, advanced analytics, and data project management.
It is especially designed for:
-
Technology professionals who want to specialize in big data and evolve toward roles related to data engineering and data projects.
-
Technical or analytical professionals seeking to expand their competencies in advanced analytics and data technologies applied to the business environment.
-
Individuals interested in gaining a comprehensive perspective to participate in or lead data-driven projects within organizations.
-
Graduates in STEM fields looking for a practical specialization aligned with current market demands.
-
Companies that wish to train or update their teams’ skills in big data technologies and projects.
Companies interested in training multiple professionals can inquire about specific conditions for corporate training and joint enrollment programs.

Who it’s for?
The Master’s in Big Data Projects is aimed at both professionals who wish to specialize in the field of data and companies interested in enhancing their teams’ skills in big data technologies, advanced analytics, and data project management.

It is especially designed for:
-
Technology professionals who want to specialize in big data and evolve toward roles related to data engineering and data projects.
-
Technical or analytical professionals seeking to expand their competencies in advanced analytics and data technologies applied to the business environment.
-
Individuals interested in gaining a comprehensive perspective to participate in or lead data-driven projects within organizations.
-
Graduates in STEM fields looking for a practical specialization aligned with current market demands.
-
Companies that wish to train or update their teams’ skills in big data technologies and projects.
Companies interested in training multiple professionals can inquire about specific conditions for corporate training and joint enrollment programs.
Why Big Data?
The management of large volumes of information, the diversity of sources, and real-time analysis increasingly require companies to use technologies capable of delivering speed, scalability, and versatility in data processing.
Proper data management provides organizations with a competitive advantage and a return on investment that justifies investing in this type of solution.
Big data makes it possible to transform data into knowledge, improve decision-making, and generate strategic value for companies. For this reason, specialized professionals in this field are increasingly in demand.
Career opportunities
-
Data Engineer
-
Big Data Engineer
-
Machine Learning Engineer
-
Data Scientist
-
Analytics Engineer
-
Data Architect
-
Big Data Consultant
-
Data Project Manager
Studying at UPM
Learning from the best
Our teaching staff is made up of young professors with a strong academic background and professional experience in different areas of data study and management.

Associate Professor

Associate Professor

Associate Professor

Full Professor

Associate Professor

Data Engineer

Assistant Professor

Assistant Professor

Assistant Professor
Curriculum
The master’s program consists of 4 compulsory modules, with a total workload of 60 ECTS credits.
Module 1
15 ECTS
Fundamentals
In this module, a series of fundamental concepts in mathematics, programming, and artificial intelligence are reviewed. It provides the foundation for the subsequent modules.
-
Introduction to Big Data and Data Governance
-
Programming for Data Science
-
Mathematics for Data Science
-
Statistics for Data Science
-
Optimization and Neural Networks

Module 2
15 ECTS
Data Management
In this module, data management is studied in depth. It begins with an introduction to databases and continues with data analysis and data visualization.
-
Machine Learning
-
Programming for Data Science
-
NoSQL Databases
-
Data Analysis with Spark
-
Management and Visualization of Large Data Sets

Module 3
15 ECTS
Advanced Concepts
In this module, students dive into advanced concepts in machine learning and deep learning. Convolutional and recurrent neural networks, as well as advanced architectures, will be studied.
-
Natural Language Processing (NLP)
-
Deep Learning
-
Master’s Thesis

Module 4
15 ECTS
Laboratories and Seminars
In this module, students will attend laboratories and seminars on current technologies used in the industry.
-
Design of products based on big data solutions
-
Big data product lifecycle planning
-
Systems architecture
-
Quantum computing applied to Machine Learning
-
Cloud computing for big data
-
Real-time data analysis
-
Specialized seminars

Curriculum
The master’s program consists of 4 compulsory modules, with a total workload of 60 ECTS credits.
Module 1
15 ECTS
Fundamentals
In this module, a series of fundamental concepts in mathematics, programming, and artificial intelligence are reviewed. It provides the foundation for the subsequent modules.
-
Introduction to Big Data and Data Governance
-
Programming for Data Science
-
Mathematics for Data Science
-
EStatistics for Data Science
-
Optimization and Neural Networks
Module 2
15 ECTS
Data Management
In this module, data management is studied in depth. It begins with an introduction to databases and continues with data analysis and data visualization.
-
Machine Learning
-
Programming for Data Science
-
NoSQL Databases
-
Data Analysis with Spark
-
Management and Visualization of Large Data Sets
Module 3
15 ECTS
Advanced Concepts
In this module, students dive into advanced concepts in machine learning and deep learning. Convolutional and recurrent neural networks, as well as advanced architectures, will be studied.
-
Natural Language Processing (NLP)
-
Deep Learning
-
Master’s Thesis
Module 4
15 ECTS
Laboratories and Seminars
In this module, students will attend laboratories and seminars on current technologies used in the industry.
-
Design of products based on big data solutions
-
Big data product lifecycle planning
-
Systems architecture
-
Quantum computing applied to Machine Learning
-
Cloud computing for big data
-
Real-time data analysis
-
Specialized seminars
FAQ
In this section you will find some of the most frequently asked questions that may help resolve your doubts. If you cannot find the answer you are looking for and need more information about the program, please feel free to contact us by filling out the contact form. We will be happy to help you.
To access the master’s program, it is necessary to hold a university degree (Bachelor’s degree in fields such as Engineering, Architecture, or similar qualifications).
In addition, due to the content of the program, it is recommended to have:
- Basic programming knowledge
- Basic knowledge of mathematics and statistics
If you have questions about the admission profile, the master’s team can guide you during the pre-registration process.
- The program lasts 9 months, with a workload of 60 ECTS credits divided into 4 modules.
- The master’s program is delivered in two weekly sessions of four hours each:
- Fridays: 16:00 – 20:00
- Saturdays: 9:00 – 13:00
- The program is delivered online and partially asynchronous. This means it is not necessary to travel to the South Campus of the Polytechnic University to attend classes, as all teaching is conducted remotely.
- In addition to the live synchronous sessions, the program includes online resources and materials that students can consult and work through independently, allowing them to adapt their study schedule to their own pace and availability.
- The total cost of the program is €5,000.
- To facilitate access to the program, the fee can be paid in two installments with no additional cost:
- €3,500 in September, when completing the enrollment process
- €1,500 in January
- This system allows the payment to be spread out more comfortably while maintaining the same total price with no extra charges.
Yes. Discounts are available for companies depending on the number of participants enrolled in the program.
Organizations interested in training several professionals can request specific information about conditions and discount options. These will be evaluated individually according to the number of enrollments and the company’s needs.
For more information, we recommend contacting the master’s team through the contact form.
- The first step is to pre-register for the program through the registration link available on this page.
- The pre-registration period for the 2026–2027 academic year will open during the second half of February 2026.
- Once the pre-registration has been completed and the application has been validated, you will receive a payment letter by email, which is required to finalize the enrollment.
- The enrollment period will be open from July 20 to September 30, 2026, during which the payment must be completed to finalize the registration.
- Classes begin on September 25, 2026, and end on July 24, 2027, according to the established academic calendar.
- This master’s program is an opportunity to boost your professional profile and develop new skills. Get ready to learn, create, and above all, enjoy the process.

