Why AI master's degrees in Spain aren't worth your money

Today we're talking about an opinion that's very much my own. My opinion is heavily skewed by bad experiences, so take it with reasonable doubt and form your own from the data below. When I started my doctorate at the School of Architecture in Madrid, back in the late nineties, I was beginning to hear talk of Bologna, of master's degrees, of how they shaved years off the undergraduate course only to sell you the shavings back as a compulsory master's. I understood none of it at the time. The picaresque tale of Lazarillo de Tormes had finally reached the university. An old professor of mine summed it up after I'd already finished my degree, with a line I've never forgotten: "Why would I give you something for free if I can charge you for it legally?" That spirit has been rotting the Spanish university for several decades. Do you notice it in the online AI master's at 13,000 euros? I do.

What these master's degrees sell

The syllabus is usually published on the university's website. Take any of the big private online schools and open its programme. You'll find:

An introduction to Python for data analysis. Pandas, NumPy, matplotlib. That's in Kaggle's free course.

An introduction to classic machine learning. Regression, trees, random forest, SVM. That's the entire content of Stanford's CS229 course, available free with all the notes, videos and problem sets.

An introduction to deep learning. Neural networks, backpropagation, convolution, attention. That's what Fast.ai covers in its free course, with code and notebooks ready to run.

An introduction to language models and applications. How to use the OpenAI API, prompts, RAG, basic fine-tuning. That's in the official OpenAI and Anthropic documentation, and in Hugging Face's free course.

A final project the student has to submit.

Let's put numbers to it, carefully. An official AI master's at a public university costs a few hundred euros: the one in Logic, Computation and Artificial Intelligence at the University of Seville, 60 credits, has public fees of around 800 euros. At the other extreme, the big business schools' programmes on AI and data analytics run into five figures, by what they themselves publish on their sites. The private online band, judging by their catalogues, tends to sit between a few thousand and the high tens of thousands of euros. For content that has a free equivalent in English.

Who teaches these courses

Here's the trap the search results don't show.

My impression, after looking at many profiles, is that a good chunk of the faculty at private online master's rotates between several institutions at once. I'm not talking about anyone in particular nor accusing any school; I'm describing a pattern anyone can check by taking a stroll around LinkedIn. When the same teacher turns up giving classes at three, four or five different centres, the most likely explanation isn't that they're an exceptional researcher their institutions are fighting over. It's that they're paid by the hour and need to pile up hours to reach a reasonable salary.

The operational consequence, if that pattern is real, is direct. Feedback to the student drops. Marking gets outsourced to tutors who aren't even the course's teachers. The commitment to updating content falls, because renewing materials for several different centres is unworkable for one person. And the syllabuses sit frozen year after year.

When you see a profile listing half a dozen AI master's spread across as many centres, don't read accumulated prestige into it. Read it, at least as a hypothesis, as a sign that the teacher is splitting their time between several institutions so the maths of their pay packet adds up.

The search-results trap

This is the least visible part and the most important. In the trade it's called SEO — search engine optimization — but the honest translation would be "how to grab the top spots when someone searches for AI master".

Private online universities dominate those top Google spots for terms like "AI master", "best AI master", "online AI master", "artificial intelligence master price". Not because they're the best programmes. Because they pour six-figure sums a year into paid advertising and organic positioning.

A Google Ads click for that keyword in Spain is expensive — the cost per click for terms like that can comfortably top ten euros, depending on which estimation tool you check. A single conversion — one enrolled student — pays for hundreds of unconverted clicks. The funnel is optimised for conversion, not for education.

When you search "best AI master Spain" you invariably find:

Master's comparison sites whose usual business model is affiliation: they're paid by the very universities they list every time a user clicks or enrols. When the income depends on the link, the order tends to answer to who pays, not to academic quality.

"Sponsored content" articles dressed up as editorial neutrality, published in the commercial sections of general-interest media. You recognise them because they always lead to the same three or four institutions, and the keywords are crowbarred in.

The official pages of the universities themselves, with the technical positioning better optimised than any public centre's — because they pay specialist agencies.

What you don't find: the sites of the UPM, the UPC, the UAM. Their master's are more serious and Google's ordering buries them, because the public university doesn't compete on advertising budget.

The free alternative (and better)

Four months of serious dedication to the following sources is worth more than ten paid master's.

Fast.ai (Jeremy Howard, Rachel Thomas). A practical deep-learning course of around eight lessons, with a second part that's even longer. Uses PyTorch, fastai, Hugging Face Transformers, Gradio. It inverts the traditional pedagogy — the first lesson trains an image classifier before explaining what a neural network is. All the code in ready-to-run notebooks. Free.

Stanford CS229. Andrew Ng's classic machine-learning course. All the notes, videos, problems and exams are published. It covers the mathematical foundation rigorously. If you're interested in understanding why something works, not just how to use it, this is your place. Free.

Neural Networks: Zero to Hero (Andrej Karpathy). Karpathy was a founding member of OpenAI and director of AI at Tesla. His YouTube series goes from derivatives to GPT, step by step, writing the code from scratch. It's probably the best free technical resource ever published for understanding language models from the inside.

MIT — course 6.034 Artificial Intelligence, available on MIT OpenCourseWare with lecture notes, exercises and exams. And 6.S191 Introduction to Deep Learning, which MIT distributes mainly through its own site (introtodeeplearning.com) and YouTube, not OCW.

Hugging Face NLP Course. Covers transformers, fine-tuning, deployment. Built for immediate practical use.

arXiv for papers. Papers With Code for benchmarks. OpenReview to follow the academic debate.

Four serious months with these sources leave you at a technical point equal to or above any private online master's at 13,000 euros. The difference is the diploma. The difference isn't the knowledge.

The language obstacle

"But all of that is in English." Yes. And so is the field's technical documentation. And the papers. And the models. And the forums where what matters gets discussed.

Learning to read technical English isn't optional for anyone who wants to work in AI. It's a prerequisite. Trying to skip it by paying for a master's in Spanish is the equivalent of paying for a low-quality translation of something you'll have to read in the original sooner or later.

DeepL does decent passes from English into Spanish if reading directly is beyond you. ChatGPT or Claude will explain dense paragraphs if you paste them in. The language barrier a student had in 1998 no longer exists. What's left is laziness, reconverted into demand for a master's in Spanish at 13,000 euros.

When paying does make sense

There are cases where paying makes sense. Three, specifically.

When it comes from a centre accredited in research. Official master's from the UPM, UPC, UAM, UC3M, UB, UAB. They have an academic board, doctoral students behind them, indexed publications in their research groups. Being official, their fees are governed by each region's public prices and rarely come close to what the private online offer charges. And the seal does carry weight.

When it includes physical laboratories you can't access on your own. Robotics programmes with real equipment, AI-applied-to-biomedicine programmes with real hospital data, computer-vision programmes with cameras and proprietary datasets.

When the goal is the network, not the content. The big business schools play in another price league — their executive programmes on data and AI run into five figures, at the high end of the market. If that outlay opens up a network of executives worth more than what you pay, that decision is yours. But let's be clear: what you're buying isn't technical training, it's access to a professional circle. The programme is the excuse.

If the master's brochure talks more about employability than about research faculty, if the word "innovation" appears more than "paper", if the "teaching staff" are LinkedIn profiles with five universities each, if there's no research group behind the programme — it isn't training. It's product. And the product doesn't cost what it's worth, it costs what the company can bill to the priciest lead its advertising delivers.

There'll be exceptions. There'll be devoted teachers doing their job well in one of those programmes. I've found, online, papers and doctoral theses from some Spanish universities that were dire, and others brilliant with the UPM, UPC or UAM seal. The average is what it is. The exception doesn't save the average. Look at the data yourself. Yours.

Quick definitions

SEM: search engine marketing. Paid advertising on Google and Bing. You pay per click.
SEO: organic search positioning. You pay for the technical optimisation, not for each click.
CPC: cost per click. What the advertiser pays each time a user clicks their ad.
Lead generation: the process of obtaining qualified contacts (name, email, phone) interested in a product.
Official master's: a programme accredited by ANECA, equivalent to 60-120 ECTS credits, giving access to a doctorate.
In-house master's / título propio: a university programme without ANECA accreditation. Doesn't give access to a doctorate. Most private online AI master's are of this kind.
Job placement service: a university service connecting graduates with job offers. Its real effectiveness varies enormously. The "ninety-something per cent" employability figures that appear in many brochures are rarely audited independently.

References

Fast.ai — Practical Deep Learning for Coders, course.fast.ai. For the content and structure of the free course.
Stanford CS229 — Machine Learning, open materials.
Karpathy, A. — Neural Networks: Zero to Hero, YouTube series. His career (founding member of OpenAI, director of AI at Tesla between 2017 and 2022) is documented in his Wikipedia entry, en.wikipedia.org/wiki/Andrej_Karpathy.
MIT OpenCourseWare — course 6.034 Artificial Intelligence, ocw.mit.edu. MIT 6.S191 Introduction to Deep Learning, introtodeeplearning.com.
Hugging Face — NLP Course.
ANECA — accreditation reports.
University of Seville — Master's in Logic, Computation and Artificial Intelligence, us.es. For the public fees of an official AI master's. The public price of a master's credit at Andalusian universities is around 13-14 euros (Andalusian regional government's public-prices decree), which gives the order of magnitude of a few hundred euros for a 60-credit master's.
IE — Programa Dirección Data, Analytics & Inteligencia Artificial, ie.edu. Referenced for the order of magnitude (five figures) of the big business schools' executive programmes on data and AI.

Elsewhere

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