Master Data Science

IMMUNE Technology Institute (IMMUNE)

  • Location Madrid, Spain
  • Degree Type MSc
  • Start Date Request info
  • Duration 6 months
  • Application Deadline Request info
  • Language Spanish
  • Attendance Blended
  • Dedication Part-time
  • Pace Instructor-paced
  • Tuition fees 8500 €

Program description

Ayuda Early Bird del 20% de descuento si comienzas el proceso de admisión en este mes. Podrás aplazar el pago del curso, sin comenzar a pagar hasta Marzo. Fecha de convocatoria: 5 de Marzo 2021.

The Data Science Master is a 420-hour on-site and online program aimed at IT professionals that seek to learn the main Artificial Intelligence techniques and how to apply them into different industry cases.

Who is this program for?

Student profile. IT professionals with developing experience that aim to:

  • Become THE Data Science expert of your company.
  • Re-skill and of your IT gaining deeper knowledge of Data Science.
  • Solve a specific problem in their company.

Company profile

  • Tech companies and startups that want to master data science methods and applications to provide better services to their clients.
  • Companies of any industry aiming to empower their IT or Operations teams to better understand the company’s data and transform into meaningful information that will empower and give them advantage over their competitors.
  • Companies of any sector that are in the process of Digital Transformation and want to level up their team’s leadership and knowledge.

What will you learn?

This program starts with the preparation of data (analysis and cleaning) using Python and R.

Then students will learn how to find meaningful information by navigating through different methodologies such as historic human labels, clusters, segmentations and patterns.

Finally, deep learning will be applied to tackle more complex data followed by data visualization.


Case to be Solved

Distributed in 5 modules, you will learn starting from the security basics, platforms, applications and incident responses to the future of cyber security and cyber intelligence.

Soft Skills

The IMMUNE methodology goes beyond technology and includes a Human Sciences perspective with aspects such as Data Visualization and Presentation Skills.

Learning by Doing

Distributed in 5 modules, you will learn starting from the security basics, platforms, applications and incident responses to the future of cyber security and cyber intelligence.

Academic Plan


Start by learning the coding fundamentals in Python. You will understand Object Oriented programming and confidently work with Python data structures: lists, dictionaries, sets, tuples, and more.

Introduction to AI. Key mathematical concepts

Introduces the basic concepts in Artificial Intelligence (AI) and the basic mathematical concepts in algebra and statistics that are key to understand the rest of the topics in the course.

The module starts with the basic concepts in AI, history, evolution and state-of-the-art in AI, together with customer examples.

Finally the key concepts in algebra and statistics will be taught with the focus on its applications to AI.

Data manipulation and analysis

This module covers the key libraries in Python and the basics in R.

The module consists in learning data access, preprocessing and exploratory analysis to understand the content of the data.

The focus for Python will be around variables, simple data structure, conditional lists, dictionaries and functions with the focus in analysis and cleaning of data.

Supervised machine learning. Classification and regression

We will cover supervised learning. This type of learning requires human intervention for the creation of labels in the historical data.

In this way the machine will be able to predict a result based on this data.

An industry case will be developed to apply your knowledge.

Unsupervised Machine Learning

We will cover the unsupervised machine learning methods which focus on historical data that have not been labeled. The objective is to find patterns and structures hidden in the data. A common example is the customer segmentation with similar attributes for marketing campaigns.

In this module the main techniques of unsupervised learning will be used with special focus on clustering, dimensionality reduction and association rules.

Data Visualization

We ill cover the visualization of data using Python and R libraries. The main libraries will be used together with a grafo visualization.

This module also includes 3D graphics and how to create them with Python.

At the end of the module additional knowledge will be provided around key open source and commercial tools which do not require programming.

Deep learning and neural networks

You will learn the basic principles of Deep Learning together with the knowledge of key algorithms. You will understand the concept of a neural network and the behaviour of data when applying these kind of methodologies.

We will go over the Densely Connected Network, convolutional neural network (CNN) and recurrent neural network (RNN).

You will learn about the unsupervised neural network and the autoencoder concepts, GANs and Boltzman machines.

AI life cycle & commercial tools

The last module encompasses the life cycle of AI in real projects. From the access to data, preprocessing and analysis training to its deployment in production.

Additionally, trendy topics in AI will be included in this module such as ethics, regulation and the future challenges.

Finally, this module examines the key tools in the market around AI with a focus in the life cycle usage.

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