As Artificial Intelligence (AI) continues to revolutionise industries, the demand for professionals who can bridge the gap between AI technology and business strategy has never been greater. The International Master in AI for Business is designed to equip graduates with the skills and knowledge to navigate this evolving landscape. This comprehensive programme blends technical expertise with business acumen, preparing students for a range of professional opportunities.
To provide deeper insights into the programme, the Co-Programme Director of the Master in AI for Business – Ignacio Anguita Espadaler – explains key aspects, from the curriculum structure to the skills developed and potential career paths.
Can you provide an overview of the International Master in AI for Business and its unique value proposition?
The International Master in AI for Business aims to prepare students for the age of AI. We combine business and management courses so that our students first become familiar with business concepts, understand the terminology, and address the challenges that arise in this environment.
Once our students are acclimatised, they begin building their technical skills to apply this business knowledge in solving problems through data analysis techniques and AI models.
Our value proposition lies in preparing students for a time when knowledge of business alone will not suffice, and they will need to automate and streamline their work. Each year, we observe an increasing number of traditional companies, such as banks, requiring their analysts to have skills like Python programming, enabling them to automate processes and analyse data for decision-making.
How does the curriculum balance technical AI skills and business strategy?
The curriculum is divided into three trimester modules:
- First Trimester: Students learn Python and are introduced to management disciplines.
- Second Trimester: Students advance their Python skills, focusing on analysing large datasets, using databases, and learning the fundamentals of machine learning.
- Third Trimester: The focus shifts to AI, exploring deep learning, creating RAGs (Retrieval Augmented Generation), building applications with LLMs (Large Language Models), and delving into advanced topics such as Machine Learning Operations.
How does the programme stay updated with the rapidly evolving AI industry?
The programme stays current thanks to our professors, who are either PhD researchers in the AI field or industry professionals.
PhD researchers teach the theoretical aspects of AI and machine learning, leveraging their expertise. Industry professionals focus on the practical applications of these technologies, sharing real-world experiences and projects that utilise the latest tools.
This dual approach ensures that students acquire both academic knowledge and industry-relevant skills, equipping them to meet contemporary standards in the AI field.
Our goal is to develop well-rounded professionals who understand business needs and can either deliver practical applications themselves or lead teams developing AI solutions to address business challenges.
What core competencies and AI integration skills will participants develop throughout the Master’s?
Participants will develop two key areas of competency:
- Business and Management Skills: These are cultivated through EADA’s renowned courses during the first trimester and sessions at the soft skills campus.
- Practical Technical Skills: Students will acquire the expertise to develop applications and AI models. This includes fundamental skills like Python software development and cutting-edge technologies, such as building applications connected to Large Language Models (e.g., ChatGPT) using RAG.
Our goal is to develop well-rounded professionals who understand business needs and can either deliver practical applications themselves or lead teams developing AI solutions to address business challenges.
How does the programme address the ethical implications of AI in business?
Ethical considerations are a significant aspect of AI, and at EADA, we have always prioritised ethics—first in business, then in ESG and now in AI.
Students learn the fundamentals of AI to understand how it works before exploring the European AI Act and its regulatory framework to address AI risks. They also examine the ethical implications of AI in a specialised subject, AI Ethics, which covers risks, biases, and mitigation techniques such as explainability tests and bias detection methods.
Can you share examples of the types of projects students undertake during the programme?
Each subject involves practical work resembling a project. Examples include building a robo-advisor or implementing an AI agent that analyses financial statements and performs valuations.
For the final project, students collaborate with a company to address a specific AI challenge. Recent projects have included developing chatbots to streamline customer service or improving investment strategies reliant on news article data.
All projects involve real data and deliver tangible outcomes, such as prototypes, software, or dashboards for analysis.
How do these projects reflect real-life business challenges involving AI?
Class projects simulate small-scale problems and challenges students are likely to encounter in their professional careers. Designed by industry experts, these exercises mimic real-world scenarios.
The final project involves direct collaboration with a company, where students tackle a real-life business problem. Examples include developing an application, software, or conducting an in-depth analysis.
Students gain valuable experience with real data, receive feedback from industry professionals, and learn best practices to overcome challenges. This hands-on approach is highly valued, with students often showcasing these projects as part of their professional experience during job interviews.
Are there any skills or knowledge required for prospective students?
Prospective students are not expected to be professional Python developers, as the programme provides resources to teach technical skills.
However, candidates should demonstrate an interest in technology, motivation, and a willingness to embrace challenges. As the Master’s programme is highly focused on hard skills, candidates are encouraged to explore introductory Python videos to gauge their interest.
Previous experience with Python or SQL is an advantage but not mandatory. Ultimately, motivation plays a key role, and even students from non-technical backgrounds have excelled with the right attitude.
What kind of professional roles and career paths can graduates pursue after completing the programme?
Most of our students end up working in either tech companies or consulting firms. Some of them, particularly those more interested in software engineering, tend to work as Data Engineers, a role that is gaining a lot of traction. This role involves creating pipelines to process huge volumes of data, thus paving the way for analysis and the creation of AI models.
Other students, who are more interested in research, often work on building AI models to support different business areas. Examples include recommendation engines, propensity-to-buy models, or churn models to predict which customers are likely to leave.
Finally, students who are more suited to business roles either work as Data Analysts, analysing data to answer business questions, or as consultants designing AI projects and translating business requirements into technical specifications.
One interesting aspect of the tech sector is the variety of growth opportunities it offers. In a traditional business environment, the only way to advance is to become a manager, which often involves less technical work. However, in the tech sector, growth can occur either as a manager or as a technical specialist, with roles such as Principal Engineer or Distinguished/Staff Engineer. These positions carry significant responsibilities and offer good salaries, but they focus on designing software architecture and solving complex technical challenges, rather than managing a team.
What kind of support, such as career services or networking opportunities, is available to help students prepare for their post-graduation careers?
Students have a wide network of opportunities during the master’s programme. First of all, they participate in soft skills training sessions, where they collaborate with students from other master’s programmes to enhance their network.
In addition, students will meet professors who work full-time in top-tier companies and can recommend which companies to apply to, as well as inform them about internship opportunities. On several occasions, students have started working as interns for different professors at their companies.
EADA Careers Services department also organises several events with companies, such as the careers fair, where students can submit their CVs to the attending companies.
Finally, through final project collaborations, students gain professional experience and can later apply for positions at these companies, as the companies are already familiar with their work and have prior experience collaborating with them.
Join the Future of Business and AI Innovation
The International Master in AI for Business is more than a programme—it’s a transformative journey designed to equip you with the technical expertise, business acumen, and ethical awareness needed to thrive in the evolving landscape of AI. With a curriculum tailored to balance theory and practice, hands-on projects with real-world impact, and a robust network of career support, this master’s programme ensures you’re ready to lead in the age of AI.
Don’t miss the chance to shape your future and make a lasting impact in the industry. Take the first step toward unlocking your potential as an AI-driven business leader
