Anybody who’s ever given ChatGPT or a similar AI-powered software a whirl has seen machine learning in action. Today, we’re on the cusp of a computational revolution as computer systems are being taught to do more than simply follow processes. They can learn just like humans though they can only do so using algorithms and models designed to show them what to learn and how to draw conclusions.


Those who can master machines, or more accurately, the concepts of building digital brains for machines, stand to enjoy long and lucrative careers. Glassdoor tells us that the average machine learning engineer picks up €70,318 in Germany alone, with senior-level engineers picking up close to €90,000. But to get to the point where you can work in this field, you need a Master’s in machine learning to demonstrate that you know what you’re doing. This article looks at three of the best programs for European and international students.


Factors to Consider When Choosing a Masters in Machine Learning Program


Before we dig into the courses, it’s important to highlight what we’re looking for. After all, a certificate needs to be worth more than the paper on which it’s printed, serving as tangible proof that you have the machine learning chops prospective employers desire.

  • University Reputation – A certificate from a university with a bad reputation is like word-of-mouth from a shyster – nobody trusts it. Any institution you choose needs to have a stellar reputation as a provider of high-quality programs.
  • Course Curriculum – The general concept of machine learning branches off into many different paths and specializations, each of which takes you in different career directions. By examining the course curriculum, you confirm that your program leads you down the right path rather than being something that’ll force you to course-correct in the future.
  • Faculty Expertise – The people who teach you need to have roots in the machine learning sector. Those roots can come from their experience in industry, academic success, or research, but they need to be there if your teachers are to provide the fuel to grow your academic seed.
  • Industry Connections – Machine learning already permeates through any industry that relies on data (i.e., almost all of them), so you want a university that offers links to employers. Look for internship programs, lecturers with a history of real-world experience, and careers departments designed to help you get ahead.
  • Tuition Fees – There’s no getting around the fact that a Master’s degree in any subject sets you back a few thousand euros. How many thousands depends on the nature of your course and the institution, so look for something that’s affordable and (where applicable) can provide financial aid.


Top Masters in Machine Learning Programs


With what to look for established, it’s time to look at a trio of Master’s in machine learning courses that fit the bill when examined under the lens of the above five factors.


Master of Science in Machine Learning and Data Science (Imperial College London)


Imperial College London has always held a high reputation in the UK (it was a fixture on the old show “University Challenge”) and its Master’s degree courses allow you to piggyback off that reputation. This Master’s is a 24-month program that’s offered 100% online, making it as accessible to international students as it is to English ones.


The program starts you off with theory and ethics, helping you understand the programming techniques and math that go into designing machine learning models. By the second year, you’ll start getting your feet wet with practical projects, develop mastery of unsupervised learning, and take on research projects to show you can apply what you’ve learned. The faculty has wide-ranging experience, led by Professor Michael Bronstein, the university’s Chair of Machine Learning and Pattern Recognition. His expertise has been called upon by the likes of the University of Oxford and Project CETI, meaning you’re in good hands from the course creation and guidance perspectives.


The downside is that this is an expensive course, costing international students £16,200 per year for a total of £32,400 (approx. €37,310 as of time of writing). That’s money well spent, considering you get a degree from a university that ranks sixth in the QS World University Rankings and has an alumni network that stretches to over 200,000 former students and faculty members. Financial assistance for those high tuition fees is available for Imperial’s Student Support Fund and Global Relief Fund, though both are only available to students who face unexpected financial hardship.


Master in Management of AI and Machine Learning (UBI Business School)


From a course focused primarily on theory, we move to one that takes a much more business-centric focus. UBI Business School has five-star ratings across the board from QS University World Rankings and delivers courses that help students harness their knowledge to meet the demands of modern industry.


Creating digital leads is the stated goal of the program, which it highlights through a curriculum developed by some of the world’s leading tech companies. The idea is simple – ask companies what they want and let them design a course that teaches it. First-stage students start with modules focusing on the psychology and ethics behind modern technology. By the second stage, those who choose the AI and machine learning specialization move into the fundamentals of AI, neural networks, and applying Python to large datasets. Finally, this MSc machine learning concludes with a management project, where you’ll complete a thesis and work directly either with an existing business or in the university’s Venture Creation Lab.


Tuition may be a sticking point because you need to pay €11,900 for the course, though you can get a discount if you pay upfront. UBI also offers scholarships based on merit and for special groups (i.e., people with special political associations). International students can also benefit from global inclusion and refugee scholarships designed to make education more accessible. The teaching staff, led by Dean and Professor Gaston Fornes, includes people who have over 15 years of professional experience, five of which are spent in senior leadership roles.


Master in Applied Data Science & AI (OPIT)


Don’t let the lack of the term “machine learning” in the degree’s name fool you – OPIT’s course leans heavily into machine learning. In the first term alone, you’ll learn about feature engineering, different machine learning models, and how to visualize data through Python and relevant coding libraries. But you’ll learn all of that in the context of how machine learning applies in data science, making the program ideal for practical people with one eye turned toward a data science career.


That focus on practicality continues in the second team, where you can study the applications of machine learning more directly. The third (and final) term is your thesis, which is your choice between a research project or an internship with a real-world company. Speaking of associations with companies. OPIT’s team of teachers boasts experience working with some major players, with former Google and Microsoft employees among their numbers. Again, that feeds into the applied approach brought to this Master’s in machine learning as you’ll learn from people who’ve actually applied what they’re teaching you.


Tuition fees are also reasonable for this 18-month course. Most can expect to pay €6,500, though early bird discounts are on offer to bring the price closer to the €5,000 range if you apply several months before the October intake. You can also pay in installments.



Other Notable Masters in Machine Learning Programs


The three courses highlighted above all offer something different, with one being more theory focused, another taking on the business angle, and the third falling somewhere in between. But beyond those three, here are a few more good MSc machine learning universities to consider.


Carnegie Mellon University


As one of the world’s top-ranked AI institutions, Carnegie Mellon is ideal for those who want to study in the United States. Learning from top researchers gives you a solid pedigree that makes you more desirable to employers after your studies.


University of Oxford


The University of Oxford’s low 18% acceptance rate belies its reputation as the UK’s foremost academic institution. Simply having the word “Oxford” on your CV opens doors that other degree programs can’t.


KU Leaven


Don’t let KU Leaven’s reputation as one of the oldest Catholic universities in the world trick you into thinking it’s not the best place for the sciences. It’s a world leader in research, especially in AI and biomedical science fields.


Guide the New Wave of Machines With an MSc Machine Learning Degree


By choosing to pursue a Master’s in machine learning, you’ve put yourself on track for a career that will be lucrative and has the potential for enormous growth as more companies adopt AI. You’re also getting yourself in on (or near) the ground floor of a metaphorical building that’s going to be so high that we may not ever see the top.


The three courses here (plus the universities touched upon at the tail end of the article) offer differing paths into machine learning. But all three give you the same result – an MSc machine learning qualification you can use to build a superb career.

Related posts

Wired: Think Twice Before Creating That ChatGPT Action Figure
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 12, 2025 6 min read

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  • Wired, published on May 01st, 2025

People are using ChatGPT’s new image generator to take part in viral social media trends. But using it also puts your privacy at risk—unless you take a few simple steps to protect yourself.

By Kate O’Flaherty

At the start of April, an influx of action figures started appearing on social media sites including LinkedIn and X. Each figure depicted the person who had created it with uncanny accuracy, complete with personalized accessories such as reusable coffee cups, yoga mats, and headphones.

All this is possible because of OpenAI’s new GPT-4o-powered image generator, which supercharges ChatGPT’s ability to edit pictures, render text, and more. OpenAI’s ChatGPT image generator can also create pictures in the style of Japanese animated film company Studio Ghibli—a trend that quickly went viral, too.

The images are fun and easy to make—all you need is a free ChatGPT account and a photo. Yet to create an action figure or Studio Ghibli-style image, you also need to hand over a lot of data to OpenAI, which could be used to train its models.

Hidden Data

The data you are giving away when you use an AI image editor is often hidden. Every time you upload an image to ChatGPT, you’re potentially handing over “an entire bundle of metadata,” says Tom Vazdar, area chair for cybersecurity at Open Institute of Technology. “That includes the EXIF data attached to the image file, such as the time the photo was taken and the GPS coordinates of where it was shot.”

OpenAI also collects data about the device you’re using to access the platform. That means your device type, operating system, browser version, and unique identifiers, says Vazdar. “And because platforms like ChatGPT operate conversationally, there’s also behavioral data, such as what you typed, what kind of images you asked for, how you interacted with the interface and the frequency of those actions.”

It’s not just your face. If you upload a high-resolution photo, you’re giving OpenAI whatever else is in the image, too—the background, other people, things in your room and anything readable such as documents or badges, says Camden Woollven, group head of AI product marketing at risk management firm GRC International Group.

This type of voluntarily provided, consent-backed data is “a gold mine for training generative models,” especially multimodal ones that rely on visual inputs, says Vazdar.

OpenAI denies it is orchestrating viral photo trends as a ploy to collect user data, yet the firm certainly gains an advantage from it. OpenAI doesn’t need to scrape the web for your face if you’re happily uploading it yourself, Vazdar points out. “This trend, whether by design or a convenient opportunity, is providing the company with massive volumes of fresh, high-quality facial data from diverse age groups, ethnicities, and geographies.”

OpenAI says it does not actively seek out personal information to train models—and it doesn’t use public data on the internet to build profiles about people to advertise to them or sell their data, an OpenAI spokesperson tells WIRED. However, under OpenAI’s current privacy policy, images submitted through ChatGPT can be retained and used to improve its models.

Any data, prompts, or requests you share helps teach the algorithm—and personalized information helps fine tune it further, says Jake Moore, global cybersecurity adviser at security outfit ESET, who created his own action figure to demonstrate the privacy risks of the trend on LinkedIn.

Uncanny Likeness

In some markets, your photos are protected by regulation. In the UK and EU, data-protection regulation including the GDPR offer strong protections, including the right to access or delete your data. At the same time, use of biometric data requires explicit consent.

However, photographs become biometric data only when processed through a specific technical means allowing the unique identification of a specific individual, says Melissa Hall, senior associate at law firm MFMac. Processing an image to create a cartoon version of the subject in the original photograph is “unlikely to meet this definition,” she says.

Meanwhile, in the US, privacy protections vary. “California and Illinois are leading with stronger data protection laws, but there is no standard position across all US states,” says Annalisa Checchi, a partner at IP law firm Ionic Legal. And OpenAI’s privacy policy doesn’t contain an explicit carve-out for likeness or biometric data, which “creates a grey area for stylized facial uploads,” Checchi says.

The risks include your image or likeness being retained, potentially used to train future models, or combined with other data for profiling, says Checchi. “While these platforms often prioritize safety, the long-term use of your likeness is still poorly understood—and hard to retract once uploaded.”

OpenAI says its users’ privacy and security is a top priority. The firm wants its AI models to learn about the world, not private individuals, and it actively minimizes the collection of personal information, an OpenAI spokesperson tells WIRED.

Meanwhile, users have control over how their data is used, with self-service tools to access, export, or delete personal information. You can also opt out of having content used to improve models, according to OpenAI.

ChatGPT Free, Plus, and Pro users can control whether they contribute to future model improvements in their data controls settings. OpenAI does not train on ChatGPT Team, Enterprise, and Edu customer data⁠ by default, according to the company.

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LADBible and Yahoo News: Viral AI trend could present huge privacy concerns, says expert
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 12, 2025 4 min read

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You’ve probably seen them all over Instagram

By James Moorhouse

Experts have warned against participating in a viral social media trend which sees people use ChatGPT to create an action figure version of themselves.

If you’ve spent any time whatsoever doomscrolling on Instagram or TikTok or dare I say it, LinkedIn recently, you’ll be all too aware of the viral trend.

Obviously, there’s nothing more entertaining and frivolous than seeing AI generated versions of your co-workers and their cute little laptops and piña coladas, but it turns out that it might not be the best idea to take part.

There may well be some benefits to artificial intelligence but often it can produce some pretty disturbing results. Earlier this year, a lad from Norway sued ChatGPT after it falsely claimed he had been convicted of killing two of his kids.

Unfortunately, if you don’t like AI, then you’re going to have to accept that it’s going to become a regular part of our lives. You only need to look at WhatsApp or Facebook messenger to realise that. But it’s always worth saying please and thank you to ChatGPT just in case society does collapse and the AI robots take over, in the hope that they treat you mercifully. Although it might cost them a little more electricity.

Anyway, in case you’re thinking of getting involved in this latest AI trend and sharing your face and your favourite hobbies with a high tech robot, maybe don’t. You don’t want to end up starring in your own Netflix series, à la Black Mirror.

Tom Vazdar, area chair for cybersecurity at Open Institute of Technology, spoke with Wired about some of the dangers of sharing personal details about yourself with AI.

Every time you upload an image to ChatGPT, you’re potentially handing over ‘an entire bundle of metadata’ he revealed.

Vazdar added: “That includes the EXIF data attached to the image file, such as the time the photo was taken and the GPS coordinates of where it was shot.

“Because platforms like ChatGPT operate conversationally, there’s also behavioural data, such as what you typed, what kind of images you asked for, how you interacted with the interface and the frequency of those actions.”

Essentially, if you upload a photo of your face, you’re not just giving AI access to your face, but also the whatever is in the background, such as the location or other people that might feature.

Vazdar concluded: “This trend, whether by design or a convenient opportunity, is providing the company with massive volumes of fresh, high-quality facial data from diverse age groups, ethnicities, and geographies.”

While we’re at it, maybe stop using ChatGPT for your university essays and general basic questions you can find the answer to on Google as well. The last thing you need is AI knowing you don’t know how to do something basic if it does takeover the world.

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