The first hybrid program in advanced analytics designed especially for operations and production process professionals.

March 18, 2024 – Open Registration


Who is the target audience?

The power of Advanced Analytics applied to the reality of Industry 4.0

Who is it aimed at and why?

The program is intended for all middle managers responsible for production and management processes in the industrial sector.

The objective is to prepare them for the new challenges of Industry 4.0 and especially those related to advanced analytics and the value of data in industry.

Results for the professional

With our executive Program, professionals will be able to acquire skills in design, implementation and operation of data Analytics projects in the industrial environment.

Personal and professional growth

The Executive Program Big Manufacturing Analytics is a great development opportunity for you, thanks to:

  • first-class faculty and facilities
  • Theoretical knowledge and case studies applied in leading companies in their sector.
  • latest trends and practices in the world of Advanced Analytics and Big Data

With the guarantee of:

Get trained and start applying the digital transformation in industry 4.0


Hybrid format training.
Duration: 1 four-month period

Remote theory sessions (4 hours per week)

Face-to-face sessions in which practices will be developed on real cases of application of advanced analytics in an industrial environment.

Block 1


This block will refresh the basic concepts of industrial plant management and improvement to unify concepts such as plant efficiency (OEE), classic improvement methodologies (Lean, Six Sigma, etc.), basic concepts of analytics and Business Intelligence.

Practice 1


The internship, with a Datatom structure, will focus on sensor data capture and dashboarding using Business Intelligence tools.

Block 2. Part I

Data Analytics in the industrial plant.
Predictive models

The objective is to deepen in Artificial Intelligence and Machine Learning concepts, and their application to the resolution of cases in the industrial environment (quality, failures, demand prediction, etc.).

Practice 2

Predictive models

With a datatom structure, we will work on the elaboration of simple and practical predictive models in the industrial environment.

Block 2. Part II

Data Analytics in the industrial plant.
Predictive models

Basic knowledge of some technologies such as Blockchain, Cybersecurity and project development using agile methodologies.

TypeOrganizationSessionsTeaching hours
Remote theoretical-practical sessions2 weekly sessions3264 h
Datatom practical sessions2 weekly sessions220 h
Total3484 h

Value proposition

Real-world experience with concepts based on the latest trends and use cases that are being applied in world-class companies

Some of our teachers:

Javier Campelo

Head of Analytics & AI at aggity

With more than 15 years in the Big Data, Analytics and Artificial Intelligence sector.
Professor Master Big Data & Analytics.
Previously, he was responsible for the 4th Banco Santander platform and led the Data Strategy & Big Data services at Deloitte Spain.

Ignacio Tornos

Industrial products & manufacturing Sector Leader

For more than 20 years he has worked on improving processes using Lean and Six Sigma. Now, using aggity’s Industry 4.0 expertise, it can help companies take their management one step further. He has held management positions in consulting and industrial companies, which gives me direct knowledge of industrial operations and experience in a wide range of processes. Knowledge of an industry’s needs allows you to identify how digitization can solve specific problems.

Javier Monjas

Machine Learning & AI at aggity

With more than 15 years of experience in this world, he has participated in multiple analytics projects in the following sectors: insurance, utilities, banking, retail, pharma, telco… occupying from development to management positions.
Training is an exciting world for Javier, he is part of the faculty of five business schools where he teaches different subjects related to Machine Learning and AI.
He is convinced that it is when analytics and business come together that impactful results are achieved for companies.

Aldo Munaretto

Big Data & Architecture at Finect

With more than 20 years of experience in Big Data, DevOps and Cloud projects. Docker and Kubernets expert.
He was previously Co-Founder and CTO of Fintecch – Finect and is a lecturer in Big Data and Cloud at top schools.

Miquel Melero

Smart Factory Solutions Leader at aggity

Senior Technician in Computer Systems Administration and UPC Postgraduate Degree in Software Management and Quality. With 20 years of experience in the world of industrial computing and the last 10 years in management and leadership positions in software development departments for industry. Since 2018 leading the Industry area in aggity participating in the sale and execution of projects.

Rosa E. Lillo

Head of the UC3M-Santander Big Data Institute. (Twitter: @BigData_UC3M)

Research, Boutique Projects and Training in Big Data and Data Science. Professor of Statistics and Operations Research at UC3M. Academic coordinator of the course.

Harold Antonio Hernandez Roig

Researcher at the Department of Statistics, Universidad Carlos III de Madrid.

B.Sc. in Mathematics, M.Sc. and Ph.D. in Mathematical Engineering. Professor of statistics, R programming and machine learning techniques in undergraduate and graduate programs at UC3M. His research focuses on functional data analysis, principal component techniques and PLS regression models for data with complex domains and/or images.

Lara Quijano Sánchez

Researcher UC3M-Santander Big Data Institute. EPS Professor at UAM

PhD in Computer Engineering, specializing in Artificial Intelligence from the UCM. Specialized in data science techniques, natural language processing, recommender systems, information search and retrieval, social network analysis, sentiment analysis techniques and predictive model design using Big Data techniques. Recognized figure in the IA community where he has been able to develop a solid and significant research experience with several relevant contributions. Spanish Police Foundation Research Awards 2016-2017 and 2017-2018, for the projects:
“VeriPol, Application of automatic text-based detection of misleading language to police reports” and “HaterNet: Automatic detection and analysis of hate speech on Twitter” that have had national and international visibility in the press.

Iván González Díaz

Professor of the Department of Signal Theory and Communications, Universidad Carlos III de Madrid.

Telecommunications Engineer from the University of Valladolid, Master and PhD in Multimedia and Communications from the University Carlos III of Madrid. He develops his research activity in the field of computer vision, machine learning and artificial intelligence, mainly focused on the recognition and processing of visual data. He has been teaching for 17 years, in engineering and data science degrees and master’s degree programs, in subjects related to signal processing, deep learning and computer vision. He regularly participates in data science and machine learning courses for professionals in the banking sector.

Pablo Morala

Researcher at the Department of Statistics, Universidad Carlos III de Madrid.

Degree in Mathematics and Physics from the University of Oviedo and Master in Statistics for Data Science, PhD in Mathematical Engineering, UC3M. His research is framed in the context of interpretability and variable selection in machine learning algorithms, especially focused on neural networks and deep learning.

Sandra Benitez

Juan de la Cierva Researcher – Dept. of Statistics of Universidad Carlos III de Madrid

Graduate, Master and PhD in Mathematics from the University of Seville. Postdoctoral researcher Juan de la Cierva – Department of Statistics at UC3M. His research is based on the development of new methodologies that combine Mathematical Optimization and Statistics to extract information from data, mainly focused on Support Vector Machines (SVMs).

Belén Pulido

Researcher at IBiDat

Graduate in Mathematics from the University of Malaga and Master in Big Data Analytics from the University Carlos III of Madrid. She is currently a researcher (PhD in Mathematical Engineering) at IBiDat (UC3M-Santander Big Data Institute). She teaches statistics and machine learning techniques in undergraduate and graduate courses at UC3M. His research focuses on functional data analysis and the application of statistical techniques and machine learning.

Fill in the form and we will contact you:

Please enable JavaScript in your browser to complete this form.
Privacy Policy

Follow us!

With the guarantee of: