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Programa avanzado en IA & Data Science for Business

Live online classes
Lunes, miércoles y jueves, 18:30 a 21:30h.
Junio 2025

Necesarios conocimientos previos.

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Study Plan

Study Plan

Statistics applied to data science

This module is a cornerstone, as it provides the fundamental tools to understand and analyze data accurately and rigorously. In this module, we will understand how statistical techniques and probabilistic concepts are essential elements in data-driven decision making, learning to apply statistical methods to draw meaningful inferences, identify patterns and trends, and make reliable predictions. We will acquire skills to assess the uncertainty and risk associated with data, critical in dynamic business environments.

  • Introduction and Key Mathematical Concepts
  • Statistics Fundamentals
  • Descriptive Statistics
  • Probability Distributions
  • Linear Algebra
  • Probability
  • Fundamental Concepts
  • Estimation Methods
Advanced AI I: Machine Learning

Once the techniques to start working with Machine Learning are settled, this module will allow us to deepen the algorithms and more complex scenarios, but also teach us advanced techniques to optimize our models and face problems when the data does not help us too much in its natural state.

  • Advanced Algorithms
  • Support Vector Machines (SVM)
  • Stochastic Gradient Descent
  • Ensemble algorithms: AdaBoost, XGBoost, among others.
  • Model Optimization
  • Hyperparameter setting
  • Feature selection
  • Regularization
  • Cross-validation
  • Time Series Analysis
  • Introduction to time series analysis
  • Modeling and trends
  • ARIMA and SARIMA models
  • Networks
  • Fundamental concepts of networks
  • Learning network representations
  • Link classification and prediction
  • Reinforcement Learning
  • Concept of reinforcement learning
  • States, actions and rewards
  • Reinforcement learning algorithms
  • Anomaly Detection and Unbalanced Data Learning
  • Identification of outlier observations using statistical methods, clustering, and supervised learning
  • Techniques for handling unbalanced data, such as additional data collection, synthetic generation and modification of algorithms
Advanced AI II: Deep Learning

The Deep Learning module is the next level in machine learning, where you will explore deep neural networks and advanced architectures for tackling complex problems. Discover how these revolutionary techniques have transformed the field, enabling analysis of higher complexity data and solving challenges in computer vision, natural language processing and more.

  • Deep Learning Introduction
  • Convolutional Neural Network (CNN)
  • Recurrent Neural Network (RNN)
  • Natural Language Processing (NLP)
  • Generative Adversarial Networks (GAN)
Generative AI

The Generative Artificial Intelligence (Generative AI) module provides students with an in-depth understanding of the technologies that enable the creation of original content from existing data. The objective is to provide both theoretical knowledge and practical experience to implement generative models in different fields.

  • Generative AI Fundamentals
  • Generative AI Development and Coding
  • Generative AI Practical Applications
  • Ethics and Responsibility in Generative AI
  • Generative AI in Digital Transformation
Data Explosion: Distributed Processing in Big Data

El procesamiento distribuido ha revolucionado la forma en que gestionamos grandes volúmenes de datos, y Apache Spark se ha establecido como una de las
principales herramientas en este campo. Su capacidad para procesar datos de forma paralela y distribuida, aprovechando la potencia de los clústeres de
computación, ha hecho que sea esencial para profesionales que buscan extraer valor de la gran cantidad de información generada en la actualidad.

  • Introduction to Distributed Processing with Spark: Understand the distributed processing paradigm offered by Spark. Its ability to split tasks across multiple cluster nodes allows operations to be performed at high speed and in parallel.
  • Data Manipulation with Spark DataFrame: DataFrames in Spark are optimized structures that allow efficient manipulation of tabular data. Here it is important to know:
    • Data loading from multiple sources.
    • Column filtering and selection.
    • Aggregations and transformations.
  • Spark SQL: This Spark module provides an interface that allows you to use SQL queries to manipulate data, making it easier to analyze and obtain valuable information.
  • Data Cleaning and Preparation: Prior to any analysis, the data must be ready for use:
    • Null value detection and treatment.
    • Missing data management.
    • Data type conversion.
    • Data standardization.
  • Data Transformation and Enrichment:
    • Date and time operations to correctly handle temporal data.
    • String manipulation for formatting and transforming textual data.
    • Creation of new columns to provide additional information for analysis.

Workshop: Dashboard en un día

Workshop: Introducción a Databricks y al ecosistema Spark

Workshop: Construcción de APIs de Datos con FastAPI y Flask

Industry 4.0

The course explores the critical components and underlying technologies of Industry 4.0, a paradigm that integrates advanced digital tools within the industrial context to improve production processes and data-driven decision making. Students will learn about digital transformation and how companies can become Data Driven entities. In addition, the fundamentals of emerging technologies such as Cloud Computing, Big Data, Internet of Things (IoT) and Artificial Intelligence will be introduced, highlighting their importance and application in today's environment.

  • Digital Transformation
  • Data Driven Companies
  • Cloud Fundamentals
  • Big Data Fundamentals
  • IoT Fundamentals
  • Artificial Intelligence Fundamentals
Journey to Cloud

It provides a detailed understanding of the cloud adoption journey, including the technical, strategic and management aspects involved. Students will be guided through fundamental and advanced cloud computing concepts, effective migration strategies, and techniques for optimizing and managing cloud infrastructures. A hands-on approach will be encouraged through the design, implementation and evaluation of cloud-based solutions.

  • Cloud Computing Fundamentals
  • Key Cloud Infrastructure Components
  • Cloud Migration Planning and Strategies
  • Design and Architecture of Cloud Solutions
  • Security and Compliance Management in the Cloud
  • Cloud Operations Management and Optimization
  • Innovation and Advanced Cloud Services
Data management, innovation and entrepreneurship

This comprehensive module teaches how to strategically manage and use data to foster innovation in diverse organizational contexts. Through a combination of advanced theory and applied practice, you will study methodologies for effective data management and the implementation of innovative processes that capitalize on emerging opportunities in the technological and business environment.

  • Data Management Fundamentals
  • Business Innovation and Creativity
  • Emerging Technologies and Digital Transformation
  • Entrepreneurship & Innovative Startups
  • Innovation Project Management
Data Governance

This module provides a comprehensive overview of data governance, highlighting its importance in managing and protecting data assets within an organization. Through the analysis of frameworks and regulations, students will learn how to implement effective policies that ensure data quality, security and compliance. The module combines theory with practical case studies to teach students how to design and implement a robust data governance program that supports the organization's strategic and operational objectives.

  • Data Governance Fundamentals
  • Metadata and Data Quality Management
  • Data Governance Roles and Responsibilities
  • Data Governance Tools and Technologies
Project Management

This module focuses on project management methodologies used to effectively lead, plan and execute complex projects. Through the study of predictive and agile methodologies, students will learn to adapt to dynamic environments and manage projects that respond to stakeholder needs and business objectives. This module combines academic theory and proven project management techniques, preparing students to face real project management challenges.

  • Project Management Fundamentals
  • Agile and Predictive Project Methodologies
  • Project Planning and Execution
  • Leadership and Project Team Management
  • Digital Adaptation and Transformation in Project Management
  • Project Management in Complex Environments
Data Ethics

This course explores the fundamental ethical principles applied to data management in the digital age. It will address complex issues such as privacy, confidentiality, autonomy, and consent in the context of the growing use of data and analytics technologies. Through a combination of philosophical theory and case studies, students will learn to navigate and apply ethical frameworks in real-world situations related to data management, ensuring responsible and fair decisions in professional settings.

  • Data Ethics Fundamentals
  • Values in the Data Age
  • Ethics in Digital Democracy
  • Ethics and Responsibility in Generative AI
  • Contemporary Issues in Data Ethics

Workshop: Negocio


Módulo asíncrono en el que se habilitará el tiempo para preparar y realizar los exámenes de certificación incluidos en el programa. IMMUNE, en este caso, actúa de facilitador en la conexión entre la entidad certificadora y el estudiante, facilitando el proceso pero sin tener la autoridad sobre el examen ni las calificaciones obtenidas por los estudiantes.

Capstone Project
  • Team building.
  • Choice of topic for final project.
  • Assigning tutors.
  • Project development with assigned tutor.
  • Project delivery.
Presentación de Capstone Project

Presentation of final project before a panel of experts.

*The academic program may be subject to changes in line with the changing demand for specific skills in the market. Your employability is our goal.
Outstanding Mentors


Unai Obieta

CIO and CDO Technology and Director of Digital Transformation | Director of the AI Master's program

David Sanz

Head of Corporate Business Intelligence

Tomás Trenor

Data Analytics Director

Álvaro Barbero

Chief Data Scientist

Adrián Bertol

Head of AI, Data & Analytics for Enterprise Business

Olga Campos

Principal xTech

Mariano Muñoz

Global Head of Data

Ángel Galán

Cloud Data Analytics Director

Carlos Eduardo Chaves

Data Scientist

Javier Castellar


*We are always on the lookout for the best professionals in the sector, so the team may vary from one edition of the course to another

Certification Training

Con este programa adquirirás las competencias necesarias para trabajar en un entorno profesional. Para que puedas demostrarlo, IMMUNE te ofrece estas certificaciones oficiales de manera gratuita:

Además, al finalizar el programa, obtendrás el título de Máster en IA & Data Science y tendrás la posibilidad de elegir entre una de estas certificaciones:

Academic Information

El Máster en IA & Data Science es un programa completo dirigido a profesionales que quieren especializarse en Data Science y dominar las técnicas de Inteligencia Artificial para aplicar en las diferentes industrias.

Requisitos previos
  • Haber completado con éxito el Bootcamp de Data Analytics de IMMUNE.
  • Haber completado con éxito el Máster en Data Science de IMMUNE.


  • Tener experiencia en las siguientes competencias:
    1. Dominio del Entorno de Desarrollo de Python
    2. Comprensión de Tipos de Datos y Variables
    3. Manejo de Estructuras de Datos
    4. Generación y Manipulación de Datos Aleatorios
    5. Implementación de Estructuras de Control de Flujo
    6. Desarrollo y Uso de Funciones
    7. Date and Time Manipulation
    8. Uso de Funciones Lambda
    9. Aplicación de Expresiones Regulares
    10. Interoperabilidad con Datos JSON
    11. Habilidades en el Modelado de Bases de Datos
    12. Dominio del Lenguaje SQL para Definición y Manipulación de Datos
    13. Dominio de Técnicas de Modelado de Datos
    14. Habilidades en Procesos ETL/ELT/E
    15. Implementación de APIs para Acceso a Datos
    16. Capacidad de Realizar un Análisis Descriptivo de Datos
    17. Habilidades en la Visualización de Datos
    18. Detección y Manejo de Valores Atípicos y Datos Faltantes
    19. Análisis de Correlaciones entre Variables
    20. Aplicación del EDA en el Desarrollo de Modelos de Machine Learning
    21. Interpretación y Comunicación de Resultados
    22. Competencia en el Uso de Herramientas de Visualización
    23. Dominio del Storytelling Basado en Datos
    24. Habilidades para Gestionar el Ciclo de Vida Completo de un Proyecto de ML"
Program Aims
  • Extraer, procesar y analizar todo tipo de datos aplicando las técnicas y herramientas actuales.
  • Entender, crear y desarrollar nuevos modelos de negocio y proyectos tecnológicos basados en el valor del dato.
  • Detectar causas, patrones y tendencias utilizando analítica de datos avanzada.
  • Undertake, manage and lead data science and big data projects.
  • Presentar datos de forma visual para obtener información valiosa para resolver un problema.
  • Construir, implementar y evaluar problemas relacionados con datos usando algoritmos de Machine Learning y Deep Learning."
Competencias profesionales del programa

Las salidas profesionales varían en función de la experiencia previa en dirección y gestión de equipos, estarás preparado para los siguientes roles:

  • Data Scientist
  • Business Intelligence
  • Business Analyst
  • Data Analyst
  • Experto en inteligencia de negocio
  • Analytics Project Manager
  • Business Analytics Manager
  • Business Intelligence Manager
  • Chief Data Officer
Career Readiness

The comprehensive training we deliver to our students thoroughly prepares them for the employment market. Through a personalized syllabus, we help them develop professional skills, establish relationships with companies and sail through recruitment processes.

Learning By Doing Methodology

It focuses on the practical application of knowledge and skills to foster meaningful and lasting learning.

Una experiencia única

Utilizamos el storytelling para crear experiencias de aprendizaje memorables que conecten con las emociones de nuestros estudiantes.

The industry is on fire
+84% Improved Employment Status
+40 Monthly Job Offers
94,5% Employability
+4,7 Job Offers/Student

An innovative and vibrant Tech Hub

We are not conventional and our campus even less so.
Designed to replicate an ecosystem of startups and tech companies, we have created a Silicon Valley oasis in the heart of Madrid. Come and check it out.

Visit the Campus
Paseo de la Castellana, 89
Co-working spaces
Meeting rooms
Rest areas
Digital classrooms
Our students are working in

IMMUNE Financing

Full Payment
Pay for the course in a single installment and receive a 5% discount.

9 / 16 Interest-free Installments
Payment can be made in 9 installments for on campus courses and 16 installments for online master’s courses.

External Financing

Pay in installments, even if you are unemployed and cannot guarantee the loan.

Pay in installments, even if you are unemployed and cannot guarantee the loan.

Pay for your training through the Spanish Employment Training Foundation
*Aimed at active workers who wish to finance their program through the subsidized training program.


We are here to answer your questions!

Will the tools I need be included in the price of the program?

The tools used throughout the program are licensed for free use, in some cases because we use educational licenses and in others because it is free software.

Is there a careers and employment guidance service?

We have an employability area which, through our Talent Hub program, is responsible for supporting the efforts of our students to enter the employment market. The services we offer include resources to help you search for and prepare for interviews, English tests, resume and/or Linkedin profile guidance, interview and elevator pitch training, and access to our exclusive internship and employment pool.

Do I need prior knowledge or experience?

No prior knowledge is required since all programs start from scratch. It is advisable however, to have user-level knowledge and a keenness for technology.

What are the requirements for my computer?

You will need to have access to a laptop with a camera, microphone and minimum requirements of 8 GB of RAM and an i5 processor.

What is the Capstone Project?

The final project is where everything you have learned throughout the program is applied and consolidated. You will present the project to a panel of professionals from companies in the sector, which represents a unique opportunity for students to demonstrate their knowledge to potential employers and also to network.

What certification or qualification will I receive on completion of the course?

Once you have finished and passed the program, you will receive a diploma issued by IMMUNE Technology Institute in digital format and verifiable using blockchain technology.

Are there grants or scholarships available?

Yes, there are scholarships or study grants as well as financing options depending on students’ circumstances. Check out our scholarship and financing options.

Can the course be delivered online?

Yes, the program is delivered online with live classes. As such, you will be in direct contact and under the supervision of the teachers, which will enable you to follow the classes and interact in a flexible and natural way.

Admissions Process

Our students are characterized by their passion for technology. Our admissions process focuses on who you are, how you think, what you have accomplished, and then sharing your goals.

Our aim is to get to know you better, see what makes you unique and ensure that the IMMUNE educational model adapts to your profile.

Personal Interview
Academic Committee

Paseo de la Castellana 89, 28046 Madrid

© IMMUNE Technology Institute. All rights reserved.
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