Master in Machine Learning and Artificial Intelligence
The Master in Machine Learning and Artificial Intelligence provides professionals with the necessary knowledge to acquire a comprehensive view of the elements and tools used in AI in order to define, analyse and implement strategies and technological applications in the business world.
- 12 months
- 60 ECTS
- APRIL 2025
- Online
- SPANISH
- 7500 €
Additionally, obtain a double degree from our academic partner in Madrid, the University specialized in what the market demands.
We are the first 100% online Business School in the world to receive the QS Stars rating, obtaining the highest distinction, five QS Stars, in the Online Learning.
OBS is a member of AMBA's BGA (Business Graduates Association), an institution that recognises the academic quality of high potential Business Schools.
Objectives
OBJECTIVE 1.
IA APPLICATIONSLearn about how the different applications of Artificial Intelligence affect in both industrial and service companies, thus getting the most out of this technology in a business.
OBJECTIVE 2.
APPLICATION DEVELOPMENTUnderstand the process linked to the development of Artificial Intelligence applications and put it into practice through the AI Design bootcamp.
OBJECTIVE 3.
TECHNOLOGIESDelve into the different technologies related to artificial intelligence, analysing their impact and main points of convergence.
OBJECTIVE 4.
PROGRAMMINGLearn the necessary programming bases for the development of artificial intelligence applications, focusing on the different existing languages.
Master in Machine Learning and Artificial Intelligence Syllabus
Our programme is structured in 3 blocks and culminates with the Master’s Thesis. In addition, the student will be able to participate in two voluntary bootcamps and different additional activities during the development of the programme.
Block 1. Fundamentals of Artificial Intelligence
Block 2. Components and elements of Artificial Intelligence
Applications and Trends of Artificial Intelligence.
Master's Final Project
Bootcamp and additional activities
1. Fundamentals of Artificial Intelligence
This module aims to provide the mathematical knowledge necessary for the design of Machine Learning algorithms. Students will learn about mathematics and statistics for AI, equations, functions and graphs, linear algebra, mathematical optimization and algorithms, among others.
Professor: Moisés Cantón Jara, Intelligence Automation Solutions Architect at TrustPortal.
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This course aims to provide the necessary programming basics for the development of AI applications. The main programming language that will be used throughout the program is Python, however, students will also learn about other main programming languages for AI, operators and expressions, algorithms and control structures, as well as data structure, among others.
Professor: Lucas Fernández Aragón, Senior Software Engineer at Red Hat.
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This module aims to provide an overview of the interrelationship between Big Data, Data Science and artificial intelligence. To do so, the student will delve into topics such as the AI ecosystem, Big Data, Data science and the interrelationship between Big Data, Data Science and Artificial Intelligence, among others.
Professor: Raúl Gómez Martínez, Professor at Universidad Rey Juan Carlos.
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2. AI components and elements
This module was designed to introduce students to some of the essential Machine Learning concepts and algorithms in order to generalize patterns through the data provided. Students will delve into supervised, semi-supervised, unsupervised and reinforcement learning, as well as the main ML algorithms.
Professor: Raúl Melgosa García, Group Data & Digital Expert at Generali.
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This course will teach students about the main concepts, elements and tools for the development of Deep Learning applications. Students will learn about the main types of artificial neural networks, as well as the fundamentals of Deep Learning.
Professor: Fermín Lozano Rodríguez, Computer Vision Engineer at Airbus Defence and Space.
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This module aims to deepen into the different automatic planning systems, focusing on the characteristics of each one of them and analysing their different applications. Students will learn about classical planning, temporal planning and probabilistic planning, as well as the main applications of automatic planning.
Professor: Roberto Fuentes Dehesa, Connected Enterprise Manager, ABSA Group.
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The objective of this course is to focus on the different models and components of NLP that make communication between machines and humans possible. Students will learn about NLP models, NLP components and NLP applications, among others.
Professor: Jerónimo Molina Molina, Head of Artificial Intelligence at Helphone.
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3. AI Applications and Trends
The objective of this module is to analyse how Speech and Text Analytics applications work, as well as their impact on businesses. Throughout this course, students will learn about the main applications of Speech and Text Analytics and Cognitive Services.
Professor: Carlos Rodríguez Abellán, Lead NLP Engineer at Fujitsu.
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This module aims to distinguish the different industrial applications of artificial intelligence and its impact on the results and the relationship with consumers, as well as the different agents involved.
Professor: Jorge Chavero, Scrum Master, Design Thinking Master.
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In this course, students will delve into the different applications of artificial intelligence in service companies and its impact on the results and the relationship with customers.
Professor: Roberto Rodríguez López, Head of Artificial Intelligence Section at Técnicas Reunidas.
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Master's Final Project and Additional Activities
This program is designed to complement the content of the thematic blocks with the necessary training in order to properly integrate the information. The training is conceived from a triple perspective: technical assistance, personal support and individual and group challenges that are essential to achieve the objectives set.
Levelling course: Bases for artificial intelligence
OBS Business School offers students a levelling course that will allow them to acquire the knowledge and skills necessary to adequately follow the program. This workshop is self-directed and voluntary. However, it is highly recommended for those students that don’t come from the technical engineering sector. This course will help students identify which areas need to be reinforced.
Training complements
Prior to the start of the program, students will have two spaces where they’ll be able to find training resources that will allow them to acquire the necessary skills and tools for the proper monitoring of the course. These courses will be monitored by a teacher until the effective start of the program:
- Introduction to programming: Pythonç
- IT Infrastructures
Pre-Master Bootcamps
The student will have the opportunity to take 3 Pre-Master Bootcamps at any time of the programme. Once the course has been completed and passed, the student will receive a certificate of completion.
- Bootcamp 1. Personal Branding
- Bootcamp 2. Data Storytelling
- Bootcamp 3. Creative Thinking and Innovation
In addition, students will also have the opportunity to take these pre-master courses; however, these are available in English only:
- Building Your Professional Brand for Employability and Career Success
- Finance Fundamentals
Introductory Workshop | Campus Training
Before the start of the academic year, students will have the opportunity to attend an introductory workshop to the Campus, where they will be provided with the necessary tools and knowledge for the correct use of the platform during the academic year.
Professional Development Program (PDP)
Two weeks before the start of the academic year, students will be able to participate in a professional development program where they will work hand in hand with a teacher to develop different skills such as time management, productivity, stress management and emotional intelligence. Upon completion of the workshop, and provided that the relevant activities have been carried out, a certificate of completion can be obtained.
During six months, students must work in groups to either develop a project related to the analysis and proposal of an artificial intelligence application for a specific organization or plan a strategy in order to incorporate artificial intelligence in an organization.
Professor: David Faustino Pérez García, Multichannel Customer Relationship at Telefónica España.
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The Lifelong learning master’s degree in Machine Learning and Artificial Intelligence is complemented with conferences and seminars that are taught in each of the blocks. These additional activities are carried out by renowned professionals in business management who present their experiences and case studies through videoconferences.
Bootcamp: Levelling course: Basics for artificial intelligence
The school offers students a levelling course that will allow them to acquire the necessary knowledge and skills to adequately follow the program. This workshop is self-directed and voluntary. However, it is highly recommended for those students who come from fields other than technical engineering. Through the development of this course, students will be able to identify those areas that need to be strengthened.
Bootcamp: AI Design
This bootcamp is developed transversally throughout the program. Thus, students will have different sessions after the different modules, which will guide them through the process of designing an artificial intelligence application. This bootcamp is 100% practical.
Professor: Sheyla Rivera, Software Developer at NinjaOne.
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Bootcamp: Ethics and Artificial Intelligence
This bootcamp focuses on the concept of ethics applied throughout the process of conception, design, development and deployment of AI applications in business, laying the foundations for the different actions that must be taken not only to guarantee a positive impact on an organization, but also on the different individuals who are part of the ecosystem of any company.
Professor: Ramón Miralles López, Lawyer specialized in cyberlaw at Ecix Group.
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Company visits
During the development of the program, students will have the opportunity to attend synchronous videoconferences with experts in the area of the program. They will share their experience and provide some of the best practices in the sector.
Case studies
The practical component of the program is indispensable and complements the theoretical training. During this process, students will be able to enjoy debates on current topics of interest, simulations for decision making applied to real situations or case studies where they will be able to strengthen their problem-solving skills.
Webinars
Most of the training is done asynchronously, which means that this exchange of knowledge is done through a platform that allows sharing written texts without the need for people to be connected at the same time. Additionally, in each of the modules, synchronous sessions or 'webinars' are organized, where all participants are connected at the same time through an application, which allows the exchange of knowledge in 'real time'.
Students taking this master will have the opportunity to prepare for the following certifications:
- ICN Business IT Certification
- Scrum Certification (Product Owner & Scrum Master)
*The cost of the certifications and preparatory courses is not included in the price of the program.
Methodology
OBS has an online methodology where the core is the student. Always backed by active and internationally renowned lecturers, who share their knowledge to enhance the professional development of students through a flexible, collaborative method with personalised monitoring. The aim is to create a unique educational experience that allows the assimilation of knowledge in a practical way.
Student ON's fundamental pillar is the student and, for this reason, throughout the course students have their Programme Manager, an academic figure who accompanies them in a personalised way.
Diploma
After successfully finishing the programme, and having completed the relevant procedures, you will receive the OBS Business School diploma. In addition, and provided that you meet the established academic and administrative requirements, you will obtain a Lifelong learning Master's degree from the Universidad Internacional de la Empresa (UNIE). In order to obtain it, you must have a University Degree (Engineering, Bachelor's Degree or Diploma).
At OBS Business School we are committed to having our own degree, which allows us to quickly update and adapt the programmes in each edition to be at the forefront of the educational level demanded by companies today. Our programmes are designed for professionals who want to strenghten their management skills and learn through an international experience.
Admission Process
The fundamental aim of our admissions process is to ensure the suitability of candidates. All participants should get the most out of this learning experience, through a context in which it is possible to develop long-term relationships with classmates, faculty and alumni.
After completing the application form for one of our programmes, you will receive an e-mail with information about the School and a member of the Admissions Department will contact you to start the admission process. Once you have successfully passed the personal interview, you must submit all the required documentation to continue the admission process and certify that you meet the requirements of the student profile. After the Admissions Committee, if it is positive, you will be able to register and enrol in the programme you have applied for.
Student Profile
The students of the Master in Machine Learning and Artificial Intelligence come from different backgrounds and sectors; however, they share a common goal - the desire to enhance their management skills to boost their careers in the digital world.
