fbpx

Artificial Intelligence & Data Science Master

On-campus / Online classes live

March 2025

15 months

Free access to complementary training:

  • Generative AI Course: Prompt Engineering and Productivity
  • Introductory programming course: Python
We prepare you to get certified in:
Databricks Certified Data Engineer AssociateMicrosoft Certified Associate

Prework

Presentation of the curriculum, work tools, program operation and presentation of the group.

Study plan

Programming fundamentals

Este módulo se centra en introducir los fundamentos de la programación usando Python, un lenguaje ampliamente utilizado y versátil, que resulta ideal tanto para principiantes como para profesionales. Python se emplea en aplicaciones web, análisis de datos, inteligencia artificial, automatización de tareas y mucho más. Su sintaxis simple y legible facilita el aprendizaje y desarrollo, proporcionando una base sólida para el resto del programa.

Modules:

  • Introduction and Basic Python Features
  • Data Types, Variables and Text Manipulation
  • Python Data Structures
  • Random Data Generation
  • Flow Control Structures
  • Python functions
  • Manipulation of Dates and Times
  • Lambda Functions
  • Regular Expressions
  • Working with JSON Data
Databases

This module provides a comprehensive introduction to the world of databases, covering everything from basic modelling principles to practical implementation using SQL. Through this course, students will learn how to define, manipulate and manage data within structured database systems, using SQL as the primary tool. The goal is to equip students with the skills necessary to design efficient databases and perform complex queries to support business decisions.

Modules:

  • General Concepts and Database Modelling
  • Introduction to the SQL Standard: Data Definition Language (DDL) and Data Manipulation Language (DML)
  • Advanced SQL Standard: Subqueries and Common Table Expressions (CTEs)
  • Scripting in SQL
Data Transformation and Modelling

This module focuses on data transformation and data modelling, essential techniques for turning raw data into valuable information in business contexts. Through methodologies such as ETL, ELT, and EL, and using modelling standards such as dimensional modelling and Data Vault, students will learn how to create sophisticated data products. In addition, the course will address the use of modern tools for the orchestration of data flows and the creation of applications and APIs that enable the effective exploitation of transformed data.

Modules:

  1. Data Transformation
    • Modelling Techniques
    • ETL/ELT/EL
    • Data Flow Orchestrators
  2. Data Exploitation
    • Creating APIs
    • Data Applications
Exploratory Analysis

Exploratory data analysis (EDA) is a crucial stage in any analytics or modelling project. It helps us understand the structure, content and relationships within the data, making it easier to prepare for the development of Machine Learning models.

Modules:

  • Introduction to Exploratory Data Analysis (EDA)
  • Python Environment Configuration for EDA
  • Descriptive Statistics with Python
  • Creating Interactive Graphics and Visualisations
  • EDA applications in Machine Learning
Visualisation principles and techniques

El módulo está diseñado para proporcionar a los estudiantes una comprensión profunda de cómo transformar datos complejos en visualizaciones claras, efectivas y accionables.

Modules:

  • Introduction to Data Visualisation
  • Types of Graphics and Their Applications
  • Designing Effective Visualisations
  • Visualisation Tools
  • Interactive Visualisation and Dashboards
  • Advanced Visualisation
  • Case Studies and Applied Projects
Advanced data visualisation

Advanced data visualisation is essential for turning complex information into clear insights that support strategic decision making in a business environment. In this module, the focus is on using business intelligence tools such as Power BI and Tableau to generate interactive reports and dashboards that present valuable information to decision makers.

Modules:

  • Concept and Relevance of Storytelling in the World of Data
  • Key Elements of a Good Data Narrative
  • Tools for Effective Dashboard Implementation: Power BI
  • Python Integration for Preprocessing and Visualisation
AI Fundamentals: Machine Learning

This module sets the starting point for the world of Machine Learning, introducing you to the key concepts and essential techniques of the field. Through hands-on and applied learning, you will discover how models can unravel hidden patterns in data. The goal is to prepare you to handle more sophisticated challenges and dive into more advanced techniques in later modules.

Modules:

  • Introduction to Machine Learning (ML)
  • Life Cycle of an ML Project
  • Fundamental concepts of ML
  • Supervised Learning: Regression
  • Supervised Learning: Classification
  • Supervised Learning: Decision Tree and Random Forest
  • Unsupervised Learning: Clustering
  • Dimensionality Reduction
Statistics applied to data science

This module is a cornerstone, providing the fundamental tools to understand and analyse data accurately and rigorously. In this module, you 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.

Modules:

  • Introduction and Key Mathematical Concepts
  • Fundamentals of Statistics
    • 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 established, this module will allow us to go deeper into more complex algorithms and scenarios, but it will also teach us advanced techniques to optimise our models and face problems when the data does not help us much in its natural state.

Modules:

  • Advanced Algorithms
  • Support Vector Machines (SVM)
  • Stochastic Gradient Descent
  • Ensemble algorithms: AdaBoost, XGBoost, among others.
  • Model Optimisation
  • Hyperparameter setting
  • Selection of characteristics
  • Regularisation
  • Cross-validation
  • Time Series Analysis
  • Introduction to time series analysis
  • Modelling and trends
  • ARIMA and SARIMA models
  • Networks
  • Fundamental concepts of graphs
  • Learning graph representations
  • Classification and prediction of links
  • Reinforcement Learning
  • Concept of reinforcement learning
  • States, actions and rewards
  • Reinforcement learning algorithms
  • Anomaly Detection and Learning from Unbalanced Data
  • Identifying outliers 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'll explore deep neural networks and advanced architectures for tackling complex problems. Discover how these revolutionary techniques have transformed the field, enabling the analysis of more complex data and solving challenges in computer vision, natural language processing and more.

Modules:

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

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

Modules:

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

Distributed processing has revolutionised the way we manage large volumes of data, and Apache Spark has established itself as one of the leading tools in this field. Its ability to process data in a parallel and distributed fashion, harnessing the power of cluster computing, has made it essential for professionals looking to extract value from the vast amount of information generated today.

Modules:

  • 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 optimised structures that allow efficient manipulation of tabular data. Here it is important to know:
  • Loading data from multiple sources.
  • Filtering and column selection.
  • Aggregations and transformations.
  • Spark SQL: This Spark module provides an interface that allows the use of SQL queries to manipulate data, facilitating analysis and gaining valuable insights.
  • Data Cleaning and Preparation: Before any analysis, the data must be ready for use:
    • Detection and treatment of null values.
    • Handling of missing data.
    • Data type conversion.
    • Data standardisation.
  • Data Transformation and Enrichment:
    • Date and time operations to correctly handle time data.
    • String manipulation for formatting and transforming textual data.
    • Creation of new columns to provide additional information for analysis.
Workshops técnicos

Esta asignatura ofrece diferentes talleres para que los estudiantes exploren la aplicación de los datos a partir de casos de éxito de empresas y profesionales de diferentes industrias.

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.

Modules:

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

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

Modules:

  • Cloud Computing Fundamentals
  • Key Components of Cloud Infrastructure
  • Cloud Migration Planning and Strategies
  • Design and Architecture of Cloud Solutions
  • Security and Compliance Management in the Cloud
  • Cloud Operations Management and Optimisation
  • 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 a variety of organisational 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 capitalise on emerging opportunities in the technological and business environment.

Modules:

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

This module provides a comprehensive overview of data governance, highlighting its importance in the management and protection of data assets within an organisation. 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 programme that supports the organisation's strategic and operational objectives.

Modules:

  • Fundamentals of Data Governance
  • Metadata Management and Data Quality
  • Roles and Responsibilities in Data Governance
  • Technologies and Tools for Data Governance
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.

Modules:

  • Project Management Fundamentals
  • Predictive and Agile Project Methodologies
  • Project Planning and Implementation
  • 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.

Modules:

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

Esta asignatura ofrece diferentes talleres para que los estudiantes exploren la aplicación de los datos a partir de casos de éxito de empresas y profesionales de diferentes industrias.

Capstone Project

Team building.

  • Choice of topic for final project.
  • Assignment of tutors.
  • Development of the project with an assigned tutor.
  • Project delivery.
  • Presentation of the final project before a panel of experts.
Internships

*Modulo sujeto a aprobación de Cualificam.

Connect with the work and professional environment to develop the skills, abilities and competences acquired in the curricular development Integrate the knowledge acquired in the training programme to the job position where the student is established. To value the performance and capacity to develop in a job position.

*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.

We rub shoulders with the best

Ángel Galán

Ángel Galán

Data Science & AI Area Director | Cloud Data Analytics Director

Unai Obieta

Unai Obieta

CIO & CDO | Technology & Digital Transformation Director

Adrián Bertol

Adrian Bertol

Manager of Artificial Intelligence

Aldo Munaretto

Aldo Munaretto

DevOps Specialist

Álvaro Romo Herrero

Álvaro Romo Herrero

NLP Research Engineer

Andrés Sánchez Ruiz

Andrés Sánchez Ruiz

Medicinal Chemical PhD Student

Arrate Sáez Montero

Arrate Sáez Montero

Chief Data Officer

Caio Moreno

Caio Moreno

Solutions Architec - GenAI + ML + BigData

Carlos Eduardo Borges Chávez

Carlos Eduardo Borges Chávez

Team Leader Data Scientist

Daniel Neira Galvis

Daniel Neira Galvis

Data Engineer

David Cruz López

David Cruz López

Senior Managing Director

David Sanz Bascuas

David Sanz Bascuas

Head of Corporate Business Intelligence

Hernán Amiune

Hernán Amiune

Machine Learning Consultant

Javier Castellar

Javier Castellar

Professor

Javier Monjas Pérez

Javier Monjas Pérez

Analytical Lead

Mariano Muñoz Martin

Mariano Muñoz Martin

Global Head of Data (CDO)

Olga Campos Santamarta

Olga Campos Santamarta

Personal and professional coach

Ricardo Palacios Maya

Ricardo Palacios Maya

Head of Blockchain

Certification training

CualificamFundación para el conocimiento madrid

At the end of the programme, you have the possibility to choose between one of these certifications:

Databricks Certified Data Engineer AssociateMicrosoft Certified Associate

And these official certifications are free of charge:

Microsoft Certified FundamentalsIT Specialist Data AnalyticsCommunication Skills fot BusinessPMI Project Management Ready
ElizaCareer opportunities

Data Scientist | Business Intelligence Analyst | Business Intelligence Expert | Data Analyst | Data Engineer | Chief Data Officer


Microsoft Azure

Microsoft Certified

DP-900 and DP-100

Databricks

Databricks certified

Data Engineer Associate

Pearson

IT Specialist

Data Analytics

Communication Skills for Business

PMI Project Management Ready™

IMMUNE

IMMUNE Technology Institute

Artificial Intelligence & Data Science Master

Academic information

This programme aims to train its students in Data Science to become expert data scientists with the necessary skills to implement data-driven solutions. As companies are increasingly migrating to robust data management systems in order to reduce the impact of bad decisions by basing their projects on the analysis of the data they collect, the demand for skilled talent that can respond in a cross-disciplinary way to questions from different areas of industry is growing.

The Master's Degree in Artificial Intelligence & Data Science seeks to take advantage of IMMUNE Technology Institute's training experience and the quality of its teaching staff to respond to this demand for skilled talent. The programme covers the professional opportunities linked to the world of data, such as engineering, analysis, science and data management from a practical approach.

In addition, it has different workshops that cover the application of solutions from the experience of professionals in different industry environments. Its syllabus also includes the latest trends in the use of Artificial Intelligence to deal with more complex data, facilitating decision-making.

Perfil de acceso
  • El alumno deberá estar en posesión de un grado universitario o título equivalente.
  • Estudiantes que hayan culminado recientemente sus estudios de grado en diferentes áreas de conocimiento y que estén interesados en adquirir competencias en el manejo, análisis e interpretación de los datos para servir a los objetivos de negocio.
  • Este perfil de estudiante podrá completar su proceso formativo con las prácticas profesionales asociadas al programa (12ECTS) que pueden ser reconocibles en el caso de un perfil de ingreso “senior”.
  • Profesionales que desean adquirir habilidades en el análisis y la ciencia de datos, con tecnologías de IA y Big Data, con experiencia laboral acreditada de al menos 3 años en puestos que requieran competencias mínimas de Grado o equivalente.
  • Para este programa no es necesario contar con conocimientos previos en programación.
  • Tampoco es necesario contar con conocimientos en el área de análisis ni ciencia de datos, aunque la experiencia profesional previa en el manejo de datos puede potenciar la experiencia formativa.
Perfil de egreso
  • El alumno egresado tendrá la capacidad de recopilar, analizar y procesar datos, combinando el conocimiento técnico con el desarrollo de habilidades de gestión.
  • Podrá aplicar desde conceptos básicos de procesamiento de datos, Inteligencia Artificial y programación en Python, hasta conceptos avanzados que incluyen el trabajo con modelos Machine Learning y Deep Learning.
  • Tendrá la habilidad de utilizar datasets reales aplicando aprendizaje automático y resolviendo problemas de negocio.
  • Será capaz de generar paneles de visualización para la rápida asimilación de la información en pos de la toma de decisiones.
  • Gestionará equipos y políticas para la correcta gobernanza del dato.
Program aims
  • Extract, process and analyse all types of data using current techniques and tools.
  • Understand, create and develop new business models and technological projects based on the value of data.
  • Detect causes, patterns and trends using advanced data analytics.
  • Undertake, manage and lead data science and big data projects.
  • Present data in a visual form to obtain valuable information to solve a problem.
  • Build, implement and evaluate data-related problems using Machine Learning and Deep Learning algorithms.
Professional skills

Career opportunities vary depending on previous experience in leadership and team management, you will be prepared for the following tasks and roles:

Ability to collect, analyse and process data, combining technical knowledge with the development of management skills. Application from basic concepts of data processing, Artificial Intelligence and Python programming, to advanced concepts including working with Machine Learning and Deep Learning models. Ability to use real datasets applying machine learning and solving business problems. Generation of visualisation dashboards for rapid assimilation of information for decision making. Management of teams and policies for the correct governance of data.

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.

An alternative training

In all our content, we include a percentage of Human Sciences to connect technology with soft skills.

Learning By Doing Methodology

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

Learning paths

With IDEIA, we design customized learning paths, tailored to your experience and goals. This ensures efficient progress, focused on what you truly need.

Our learning paths guide you from beginner to expert in your area of interest. They are structured and flexible itineraries, tailored to your pace, so you can reach your full personal and professional potential.

Learning paths
Admission test

This questionnaire will allow us to get to know your profile in depth and ensure that this course is perfectly suited to your level of knowledge and expectations, guaranteeing that you get the most out of our program.

Why should you take the test?
  • To assess your prior knowledge.
  • To ensure that this course is the right fit for you.
  • To offer you a personalized and unique learning experience.
How does it work?

The test is completely online, requires no prior preparation, and will take no more than 25 minutes.

Take the test

Testimonials

Financing

IMMUNE financing

Full payment

Si realizas el pago en una sola cuota te beneficiarás de un 15% de descuento.

15 Cuotas sin intereses

External financing

Sequra

Sequra

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

Quotanda

Quotanda

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

Fundae

Fundae

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.

FAQs
This program is for you if

Do you want to level up?

Do you want to stay in your field or sector, but you want to continue learning and explore new challenges? It's time to give your professional profile a boost and align it with the latest trends in technology.

Are you finishing your degree, and you want an upgrade in technology?

We love your profile, because you dare to dream. And in the professional world, fortune favors the bold. If you are an entrepreneur or freelancer, this program will help take your professional projects to the next level.

Want to change your professional career?

If you want your career to take a new direction and enter the world of tech with a bang, the program will help you specialize and shape your professional profile.

Are you an entrepreneur or freelancer?

This program will put you in the spotlight, as technology is the engine of innovation and the key to staying competitive in a constantly evolving market.

What are the admission requirements?

It is not necessary to demonstrate any prior training for admission, only to go through the admission process consisting of an evaluation of your resume and a personal interview with our admissions team.

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.

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.

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.

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.

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.

1. Application
2. Personal interview
3. Academic committee
4. Enrollment
Request informationStudy planCertificationsAcademic informationFinancingFAQs
IMMUNE Campus

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
+2000m²
Paseo de la Castellana, 89
Co-working spaces
Meeting rooms
Rest areas
Digital classrooms
Auditorium
Recording studio
Subscribe to our newsletter
menuchevron-down