First term
The Master’s in Artificial Intelligence is structured over two terms. The first, comprising a total of 36 credits(6 per module), is designed to build in-depth, cross-disciplinary knowledge. It is not just about learning to programme, but about understanding the ‘why’ behind each mathematical model and the business context in which each AI solution will be applied.
AI in the Business World
An AI model is only valuable if it solves a real business problem. This module provides you with the strategic vision to achieve this. You will explore how AI is revolutionising entire industries and learn how to implement effective data governance to ensure the quality and reliability of information.
You will receive training in project management using agile methodologies, enabling you to adapt to change and deliver value on an ongoing basis. Finally, you will address the crucial ethical and legal aspects of AI and MLOps, the discipline that integrates models into a company’s production systems in a scalable and efficient manner.
Mathematics and Statistics for AI
All artificial intelligence is underpinned by a robust mathematical and statistical foundation. This module goes beyond theory to immerse you in the techniques you will need to work with big data. You will learn to apply estimation theory to make accurate inferences, to use Bayesian statistics to update your models with new evidence, and to master complex graph theory, which is fundamental for analysing social networks, recommendation systems and fraud detection.
This is the foundation that will enable you not only to use, but also to innovate with and critically evaluate any AI model. This module carries 6 compulsory credits.
Programming and Development Environment for AI
This is where theory is transformed into executable code and real-world solutions. The course will give you practical proficiency in Python, the industry-standard language for machine learning , as well as in R, which is very powerful for statistical analysis. You will become familiar with the ecosystem of essential libraries such as Pandas for data manipulation, NumPy for numerical computation, and deep learning frameworks such as scikit-learn and TensorFlow for building and training complex models.
In addition, you will acquire a crucial skill in the professional world: version control with Git, which is essential for teamwork and project management. This module is worth 6 compulsory credits.
AI Techniques: Classification and Clustering
This 6-credit module delves into two of the most important tasks in machine learning. You will learn how to ‘teach’ machines to categorise information (classification) for problems such as spam detection or medical diagnosis, and to identify hidden structures and patterns in data (clustering) for customer segmentation, for example.
You will master key algorithms such as Support Vector Machines (SVM), the k-Nearest Neighbours (k-NN) method and the popular K-Means algorithm, and you will understand the importance of feature engineering in preparing and selecting the data that will make your models truly powerful.
AI Techniques: Regression, Deep Learning and Others
This module covers some of the most powerful and advanced predictive models. You will progress from linear and logistic regression—which are fundamental for understanding relationships within data—to the fascinating world of Deep Learning.
You’ll work with recurrent neural networks (LSTM), which specialise in sequential data such as text or time series, and with convolutional neural networks (CNN), the foundation of computer vision. You will conclude with reinforcement learning, the technique that enables machines to learn to make optimal decisions through reward and punishment. This module carries 6 compulsory credits.
Programming Language
Before you can build complex machine learning models, it is essential to master the language in which machines communicate. This module is the fundamental starting point on your journey as an AI developer. Here, you will not only learn the syntax of a language such as Python – the industry standard – but you will also internalise the logic of programming, which will enable you to solve problems in a structured and efficient manner.
The course delves into algorithms and data structures (lists, dictionaries, etc.), which form the foundation for handling and processing information on a large scale. Furthermore, it lays the foundations for good coding practices, ensuring that the code you write is clean, readable and maintainable – an essential skill for any professional project.
This module equips you with the necessary proficiency so that, in subsequent modules, your sole concern will be ‘what’ you want to build, rather than ‘how’ to write the code. This module carries 6 compulsory credits.
Second term
The second term is dedicated to specialisation in high-impact areas, applying everything you have learnt to complex problems involving both structured and unstructured data. This first part of the master’s programme comprises a total of 12 credits, 6 per module.
Areas of application and use cases: environments with structured data
This module, which comprises 6 compulsory credits, specialises in one of the most valuable challenges for businesses: forecasting based on time series. You will learn to forecast demand for a product, trends in financial markets or energy consumption.
To this end, you will study everything from classic, robust models such as ARIMA and Prophet (developed by Facebook) to the most innovative deep learning architectures, such as LSTM networks and the revolutionary Transformers (Temporal Fusion Transformer), which are capable of capturing complex long-term patterns that other models cannot detect.
Areas of application and use cases: environments with unstructured data
The major challenge of Big Data often lies in information that does not come in organised tables, such as text, audio or images. This module delves deeply into Natural Language Processing (NLP), the branch of AI that teaches machines to understand and generate human language.
You will understand the evolution from RNNs and LSTMs to Transformer models, such as BERT or GPT, which have revolutionised the field. Furthermore, the approach is eminently practical, covering how to deploy these solutions in the cloud or on local devices (edge computing) and exploring the tools of the future, such as LangChain and intelligent agents. This module carries 6 compulsory credits.
A Flexible Online Approach
Just as important as what you study is how you study it. The UAX Master’s in Artificial Intelligence is delivered via a barrier-free online methodology, designed to enable you to balance your studies with your personal and professional life.
- Ongoing support: From day one, you’ll have academic advisers to guide your progress and answer your questions, so you’ll never feel alone in front of the screen.
- Total flexibility: You’ll have 24/7 access to the Virtual Campus, where you’ll find all the materials, documents and lectures. You can attend live sessions to interact with lecturers and fellow students, or watch them on demand at a time that suits you best.
- You choose how to sit your exams: In each examination session, you’ll be free to choose whether you’d prefer to sit your exams online from home or in person at the venues designated by UAX.
- The prestige of a leading university: You’ll be part of Alfonso X el Sabio University, an institution with over 30 years’ experience and a campus in Madrid at your disposal for any administrative matters.
Summary
In short, a true education in Artificial Intelligence lies in a comprehensive programme. The UAX Master’s in Artificial Intelligence, spanning 60 credits, is specifically designed in line with this philosophy: to develop well-rounded and versatile professionals, whose value lies not in a single subject within artificial intelligence, but in the synergy of all of them.
The curriculum guides you progressively, starting with a solid foundation in mathematics and programming before moving on to the applications most in demand by industry, such as deep learning and natural language processing. The aim is ambitious and clear: to train leaders with a deep understanding of business, who are aware of ethical challenges and capable of implementing AI solutions that generate a real and positive impact. By the end of the programme, rather than having simply studied isolated subjects, you will have acquired the skills to play a leading role in the digital transformation.
Sources
Curriculum for the UAX Online Bachelor’s Degree in Psychology
