Mydra logo
Log in
>All courses>Artificial Intelligence
Artificial Intelligence
IEBS Digital School logo

IEBS Digital School

Master in Artificial Intelligence and Industry 4.0

  • up to 7 months
  • Advanced

This master's program equips you with the skills to analyze and apply technologies such as AI, Robotics, IoT, and Blockchain. You will understand the concept of Industry 4.0 and develop plans for transforming your organization.

  • Artificial Intelligence
  • Robotics
  • IoT
  • Blockchain
  • Machine Learning

Overview

Gain comprehensive knowledge and practical skills in AI and Industry 4.0 technologies, including how to digitalize processes and apply improvement techniques like Kaizen and Lean Manufacturing methods such as Just in Time.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    Spanish
    course language
  • Professional Certification
    upon course completion
  • Full-time
    course format
  • Live classes
    delivered online

Who is this course for?

Plant Technicians

Responsible for manufacturing and Operations Directors of industrial companies.

CEOs and Entrepreneurs

Small manufacturing business CEOs and entrepreneurs aiming for growth and scalability.

Industry Managers

Managers seeking to acquire skills in applying new technologies and methodologies to the production process and thus become Industry 4.0 Managers.

Business Analytics and Consultants

Professionals looking to develop skills in automation and process improvement.

This master's program in Artificial Intelligence and Industry 4.0 offers cutting-edge training in the most advanced industrial technologies. You will learn to apply AI, IoT, and Robotics to modernize and enhance industrial processes, making you a leader in the digital transformation of the industry.

Pre-Requisites

1 / 2

  • University degree or equivalent demonstrable experience.

  • Desire to learn, motivation, analytical skills, and ability to work.

What will you learn?

Industry 4.0 and Digital Transformation Plan
Diagnosis and implementation of a digital transformation plan.
Fundamentals of AI and Machine Learning
Introduction to AI and Machine Learning, regression algorithms, evaluation, and metrics, ML ecosystems in the cloud.
Artificial Intelligence in the Connected Industry
AI for Industry 4.0, machine learning, neural networks, and artificial vision OCR-OCV.
Supervised Learning I
Binary and multiclass classification, metrics, ROC curve, classification with Naive Bayes and Support Vector Machine (SVM).
Robotics Applied to Industry 4.0
Robotics in Industry 4.0, collaborative robots (Cobots), basic programming, autonomous guided vehicles (VGAs).
Supervised Learning II
Classification with KNN, logistic regression, softmax, regression and classification with decision trees, classifier combination: ensembles and random forests.
IoT and Communication Systems
IoT based on microcontrollers and Linux, SCADA, MES, CMMS systems and their cloud computing evolution, Industry 4.0 protocols (OPC-UA, MQTT, CoaP, TCP).
Unsupervised Learning
Data dimensionality reduction: PCA, clustering algorithms: K-means and hierarchical, anomaly detection techniques.
Blockchain Applied to Industry 4.0
Introduction to Blockchain, implications of Blockchain in Industry 4.0, interaction between Blockchain and Industry 4.0 technologies.
Neural Networks and Deep Learning
Milestones of Deep Learning and fundamentals of neural networks, Deep Learning frameworks, types of neural networks and model tuning.
Cybersecurity Applied to Industry 4.0
Cybersecurity in IT/OT/ICS/IoT environments, cybersecurity diagnosis, good cybersecurity practices.
Convolutional Neural Networks (CNNs)
Fundamentals of CNNs: kernels, convolution, pooling, pre-trained models: Transfer Learning and Fine-Tuning, Deep Learning in production.
Recommendation Systems
AI and data-driven personalization, collaborative filtering, content-based, context-based, and hybrid recommendations, applications, trends, and challenges of recommendation systems.
Natural Language Processing
Logical and probabilistic models of NLP, use of NLP.
Master's Thesis Project
Final project integrating the knowledge and skills acquired throughout the course.

Meet your instructors

  • Jesus Andicoberry

    Instructor, IEBS Digital School

    Economist with over 30 years of experience in the ICT industry, passionate about information technologies. Consultant, advisor and trainer, helping companies in their personnel-centered digital transformation processes.

  • Juan José Silva Torres

    Instructor, IEBS Digital School

    Passionate about Data Science, Artificial Intelligence, and Machine Learning. Believes AI can significantly enhance people's lives.

  • Fernando Martín Jiménez

    Co-Founder, DOST AI

    I am fortunate to devote myself to my great passion: Innovation-oriented technology.

  • Francisco José Blanco López

    Instructor, IEBS Digital School

    Francisco José Blanco López is an instructor at IEBS Digital School, specializing in business development and Industry 4.0. He provides solutions for process automation to improve quality and increase production through collaborative robotics applications, thus enhancing competitiveness in SMEs.

Upcoming cohorts

  • Dates

    Oct 29, 2026 — May 29, 2027

€5,950