AI and machine learning are like an unstoppable tidal wave in today’s world. We’ve already seen the crest of that wave appear over the horizon with increased automation in businesses and the emergence of apps like ChatGPT. But in the coming years, the wave will engulf the world, making AI big business.


That’s supported by statistics from Statista, too, with reports that the AI market that was worth $200 billion (approx. €185 billion) in 2022 will be worth a staggering $2 trillion (approx. €1.85 trillion) in 2030. The point is that massive growth is coming in AI, and the right Master’s in AI is the key for you to be a part of that growth rather than getting stuck in an industry that gets consumed by it.


Top European Programs for Masters in AI and ML


In choosing the MSc artificial intelligence programs that appear on this list, we looked at factors ranging from the quality (and variety) of course content to who provides the degree. The three courses highlighted here are among Europe’s best to offer to European and overseas students.


Master in Artificial Intelligence (Universita di Bologna)


Though it’s held in Italy, this Master’s program is delivered in English as part of Universita di Bologna’s computer science program. It’s an on-campus course, meaning you’ll have to move to Bologna to attend.


The course provides a solid grounding in the foundations of AI over two years. You’ll get to grips with topics like machine learning and natural language processing, in addition to touching on the ethical and social issues that the rise of AI brings to the table.


The course is welcoming to international students, as it currently has a 77% ratio of international students who don’t come from Bologna. To apply, you must complete an application on the Studenti Online program, along with a mandatory form. Failure to follow this procedure leads to your application being discarded. Applicants don’t necessarily need to hold a Bachelor’s degree, though they must demonstrate a transcript of record that shows they have earned at least 150 ECTS or CFU credits in majors like computer science, mathematics, statistics, and physics.


The course page boasts that 90.5% of its 2021 graduates were happy with their degrees. It’s natural to assume most of these graduates leveraged their Master’s in artificial intelligence to move into careers in the field.


Master in Applied Data Science & AI (OPIT)


If you want to master artificial intelligence with a sprinkling of applying that mastery to the data science industry, OPIT’s course is right for you. It’s an 18-month course (though a 12-month fast-track version is available) that is fully online and delivers 90 ECTS credits. The first term covers the foundational aspects of AI, including subjects like machine learning and data science. But the second term stands out as it moves study from the theoretical to the practical by challenging you to solve real-world problems with your knowledge.


As an online program, it’s available to anybody anywhere, with entry requirements also being flexible. You’ll need a BSc degree, even one from a non-technical field, and should demonstrate English proficiency up to the B2 level with appropriate certification. Don’t worry if you don’t have an English language certification because OPIT offers its own that you can take before registering for the course.


Career-wise, the course is a good option because it occupies an interesting middle-ground between theory and practicality. The second term, in particular, equips you with skills that you can apply directly in fields as varied as IT business analysis, business intelligence, and data science.



MSc in Advanced Computer Science (University of Oxford)


Though it’s not marketed directly as a Master’s in machine learning and artificial intelligence, the University of Oxford’s program gives you excellent qualifications in both. It’s also delivered by an institution that EduRank names as the best for AI in the UK, and sixth-best in the world. The course examines advanced machine learning and computer security techniques, focusing on computational models and the algorithms behind them.


It’s a full-time program demanding 35 hours of weekly study, 15 of which you’ll spend on campus with the other 20 dedicated to self-study. It’s also a tough nut to crack for applicants, as the University of Oxford has a low 18% acceptance rate. You’ll need a first-class undergraduate degree with honors (or an equivalent) in mathematics or computer science to stand a chance of getting into one of the UK’s most prestigious universities.


Those tough entry requirements pay off later on, though, as the words “University of Oxford” on a CV immediately make employers stand up and pay attention. The wide-ranging approach of the program also means you’re not focusing solely on AI, opening up career opportunities in other fields related to math and statistical analysis.


Data Science Master – Europe’s Best Options


Data science is an industry that requires you to translate your understanding of algorithmic theory to transform complex data sets into actionable insights. It’s also an industry that’s making increasingly heavy use of AI tools, making a Master’s in data science a great companion (or alternative) to the best artificial intelligence Master in Europe. As you noticed above, OPIT’s MSc AI program includes elements of data science, though the two programs here (covered in brief) are excellent choices as standalone programs.


MSc Data Sciences and Business Analytics (Essec Business School)


This hybrid course lasts for either one or two years, depending on your background, and focuses on the application of data sciences in a business context. It’s also ranked as the fourth-best Master’s in business analytics in the world by QS World University Rankings.


That high ranking is backed up by the university’s own statistics, which state that over half of its students get jobs before they even complete the course. Essec has a 100% career success rate for graduates in less than six months from completion of the Master’s, making this a great choice for career-focused students. Google, Amazon, JP Morgan Chase, and PwC count as some of the top recruiters that keep their eye on graduates from this program.


Admission requires a degree in a related technical subject, such as engineering, science, or business, from a leading university. That degree also impacts the version of the program you take, as a three-year BSc means you take the two-year Master’s, while those who have a four-year BSc under their belts take the one-year version, assuming they meet other requirements.


Data Science, Technology, and Innovation (University of Edinburgh)


With over 13,000 international students, the University of Edinburgh welcomes overseas students who want to expand their knowledge. Its MSc data science program is no different, buoyed by the fact that it’s an online course that doesn’t require you to move to the less-than-sunny climate of Edinburgh.


It’s a part-time program that relies on self-study, though it provides you with plenty of interactive resources to help along the way. The program is something of an umbrella course as it focuses on equipping students with the knowledge they need to enter the data science field across industries as diverse as medicine, science, and even the arts.


You’ll need the equivalent of an Upper Second-Class Honors degree that has elements of programming before applying. Ideally, you’ll also have evidence of mathematical skill, either through taking math classes in your undergraduate studies or by demonstrating the equivalent of an English A-Level in math through other qualifications.

 

Factors to Consider When Choosing an Artificial Intelligence Master’s


The five programs highlighted here all help you master artificial intelligence, with many also providing a practical grounding that puts you in good stead for your future career. But if you want to do more research (and that’s always a good idea), the following factors should be on your mind when checking other programs:

  • Course Curriculum – The content of your course impacts what you can do once you have your MSc under your belt. Focus on programs that teach tangible skills applicable to the field you wish to enter.
  • Faculty – Always check the credentials of the program’s creators and administrators, particularly in terms of industry experience, to confirm they have the relevant tools.
  • Tuition and Financial Aid – Master’s programs aren’t cheap (you’ll pay several thousand euros for even an online course), so check you can budget accordingly for the program. Many universities offer financial aid options, from scholarships to student loans, that can help in this area.
  • Location – The location isn’t really an issue if you take an online course, but it impacts your decision if you decide to study on-campus. Remember that you’ll spend at least a year of your life on the course (often two years) so you need to gel well with the place in which you’ll live.
  • Networking and Industry – Does the course provider have connections to major industry players? Does it offer career advice, ideally via a specialized office or program? These are the types of questions to ask when assessing a university’s capacity for networking and career advancement.


Become a Master in Artificial Intelligence


A Master’s degree in artificial intelligence is your entry point into a growing industry that’s already on the verge of taking the world by storm. That is, assuming you choose the right program. The five highlighted here all land in the “right program” category by virtue of the tuition you receive, the reputation of the institution, and their accessibility to European and overseas students.


Research each program (and any others you consider) extensively before making a choice. Remember that it’s not always about the course or its reputation – it’s about how the course helps you achieve the specific learning goals you need to achieve to get ahead in your chosen career.

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The Yuan: AI is childlike in its capabilities, so why do so many people fear it?
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Nov 8, 2024 6 min read

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  • The Yuan, Published on October 25th, 2024.

By Zorina Alliata

Artificial intelligence is a classic example of a mismatch between perceptions and reality, as people tend to overlook its positive aspects and fear it far more than what is warranted by its actual capabilities, argues AI strategist and professor Zorina Alliata.

ALEXANDRIA, VIRGINIA – In recent years, artificial intelligence (AI) has grown and developed into something much bigger than most people could have ever expected. Jokes about robots living among humans no longer seem so harmless, and the average person began to develop a new awareness of AI and all its uses. Unfortunately, however – as is often a human tendency – people became hyper-fixated on the negative aspects of AI, often forgetting about all the good it can do. One should therefore take a step back and remember that humanity is still only in the very early stages of developing real intelligence outside of the human brain, and so at this point AI is almost like a small child that humans are raising.

AI is still developing, growing, and adapting, and like any new tech it has its drawbacks. At one point, people had fears and doubts about electricity, calculators, and mobile phones – but now these have become ubiquitous aspects of everyday life, and it is not difficult to imagine a future in which this is the case for AI as well.

The development of AI certainly comes with relevant and real concerns that must be addressed – such as its controversial role in education, the potential job losses it might lead to, and its bias and inaccuracies. For every fear, however, there is also a ray of hope, and that is largely thanks to people and their ingenuity.

Looking at education, many educators around the world are worried about recent developments in AI. The frequently discussed ChatGPT – which is now on its fourth version – is a major red flag for many, causing concerns around plagiarism and creating fears that it will lead to the end of writing as people know it. This is one of the main factors that has increased the pessimistic reporting about AI that one so often sees in the media.

However, when one actually considers ChatGPT in its current state, it is safe to say that these fears are probably overblown. Can ChatGPT really replace the human mind, which is capable of so much that AI cannot replicate? As for educators, instead of assuming that all their students will want to cheat, they should instead consider the options for taking advantage of new tech to enhance the learning experience. Most people now know the tell-tale signs for identifying something that ChatGPT has written. Excessive use of numbered lists, repetitive language and poor comparison skills are just three ways to tell if a piece of writing is legitimate or if a bot is behind it. This author personally encourages the use of AI in the classes I teach. This is because it is better for students to understand what AI can do and how to use it as a tool in their learning instead of avoiding and fearing it, or being discouraged from using it no matter the circumstances.

Educators should therefore reframe the idea of ChatGPT in their minds, have open discussions with students about its uses, and help them understand that it is actually just another tool to help them learn more efficiently – and not a replacement for their own thoughts and words. Such frank discussions help students develop their critical thinking skills and start understanding their own influence on ChatGPT and other AI-powered tools.

By developing one’s understanding of AI’s actual capabilities, one can begin to understand its uses in everyday life. Some would have people believe that this means countless jobs will inevitably become obsolete, but that is not entirely true. Even if AI does replace some jobs, it will still need industry experts to guide it, meaning that entirely new jobs are being created at the same time as some older jobs are disappearing.

Adapting to AI is a new challenge for most industries, and it is certainly daunting at times. The reality, however, is that AI is not here to steal people’s jobs. If anything, it will change the nature of some jobs and may even improve them by making human workers more efficient and productive. If AI is to be a truly useful tool, it will still need humans. One should remember that humans working alongside AI and using it as a tool is key, because in most cases AI cannot do the job of a person by itself.

Is AI biased?

Why should one view AI as a tool and not a replacement? The main reason is because AI itself is still learning, and AI-powered tools such as ChatGPT do not understand bias. As a result, whenever ChatGPT is asked a question it will pull information from anywhere, and so it can easily repeat old biases. AI is learning from previous data, much of which is biased or out of date. Data about home ownership and mortgages, e.g., are often biased because non-white people in the United States could not get a mortgage until after the 1960s. The effect on data due to this lending discrimination is only now being fully understood.

AI is certainly biased at times, but that stems from human bias. Again, this just reinforces the need for humans to be in control of AI. AI is like a young child in that it is still absorbing what is happening around it. People must therefore not fear it, but instead guide it in the right direction.

For AI to be used as a tool, it must be treated as such. If one wanted to build a house, one would not expect one’s tools to be able to do the job alone – and AI must be viewed through a similar lens. By acknowledging this aspect of AI and taking control of humans’ role in its development, the world would be better placed to reap the benefits and quash the fears associated with AI. One should therefore not assume that all the doom and gloom one reads about AI is exactly as it seems. Instead, people should try experimenting with it and learning from it, and maybe soon they will realize that it was the best thing that could have happened to humanity.

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The European Business Review: Adapting to the Digital Age: Teaching Blockchain and Cloud Computing
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Nov 6, 2024 6 min read

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By Lokesh Vij

Lokesh Vij is a Professor of BSc in Modern Computer Science & MSc in Applied Data Science & AI at Open Institute of Technology. With over 20 years of experience in cloud computing infrastructure, cybersecurity and cloud development, Professor Vij is an expert in all things related to data and modern computer science.

In today’s rapidly evolving technological landscape, the fields of blockchain and cloud computing are transforming industries, from finance to healthcare, and creating new opportunities for innovation. Integrating these technologies into education is not merely a trend but a necessity to equip students with the skills they need to thrive in the future workforce. Though both technologies are independently powerful, their potential for innovation and disruption is amplified when combined. This article explores the pressing questions surrounding the inclusion of blockchain and cloud computing in education, providing a comprehensive overview of their significance, benefits, and challenges.

The Technological Edge and Future Outlook

Cloud computing has revolutionized how businesses and individuals’ access and manage data and applications. Benefits like scalability, cost efficiency (including eliminating capital expenditure – CapEx), rapid innovation, and experimentation enable businesses to develop and deploy new applications and services quickly without the constraints of traditional on-premises infrastructure – thanks to managed services where cloud providers manage the operating system, runtime, and middleware, allowing businesses to focus on development and innovation. According to Statista, the cloud computing market is projected to reach a significant size of Euro 250 billion or even higher by 2028 (from Euro 110 billion in 2024), with a substantial Compound Annual Growth Rate (CAGR) of 22.78%. The widespread adoption of cloud computing by businesses of all sizes, coupled with the increasing demand for cloud-based services and applications, fuels the need for cloud computing professionals.

Blockchain, a distributed ledger technology, has paved the way by providing a secure, transparent, and tamper-proof way to record transactions (highly resistant to hacking and fraud). In 2021, European blockchain startups raised $1.5 billion in funding, indicating strong interest and growth potential. Reports suggest the European blockchain market could reach $39 billion by 2026, with a significant CAGR of over 47%. This growth is fueled by increasing adoption in sectors like finance, supply chain, and healthcare.

Addressing the Skills Gap

Reports from the World Economic Forum indicate that 85 million jobs may be displaced by a shift in the division of labor between humans and machines by 2025. However, 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines, and algorithms, many of which will require proficiency in cloud computing and blockchain.

Furthermore, the World Economic Forum predicts that by 2027, 10% of the global GDP will be tokenized and stored on the blockchain. This massive shift means a surge in demand for blockchain professionals across various industries. Consider the implications of 10% of the global GDP being on the blockchain: it translates to a massive need for people who can build, secure, and manage these systems. We’re talking about potentially millions of jobs worldwide.

The European Blockchain Services Infrastructure (EBSI), an EU initiative, aims to deploy cross-border blockchain services across Europe, focusing on areas like digital identity, trusted data sharing, and diploma management. The EU’s MiCA (Crypto-Asset Regulation) regulation, expected to be fully implemented by 2025, will provide a clear legal framework for crypto-assets, fostering innovation and investment in the blockchain space. The projected growth and supportive regulatory environment point to a rising demand for blockchain professionals in Europe. Developing skills related to EBSI and its applications could be highly advantageous, given its potential impact on public sector blockchain adoption. Understanding the MiCA regulation will be crucial for blockchain roles related to crypto-assets and decentralized finance (DeFi).

Furthermore, European businesses are rapidly adopting digital technologies, with cloud computing as a core component of this transformation. GDPR (Data Protection Regulations) and other data protection laws push businesses to adopt secure and compliant cloud solutions. Many European countries invest heavily in cloud infrastructure and promote cloud adoption across various sectors. Artificial intelligence and machine learning will be deeply integrated into cloud platforms, enabling smarter automation, advanced analytics, and more efficient operations. This allows developers to focus on building applications without managing servers, leading to faster development cycles and increased scalability. Processing data closer to the source (like on devices or local servers) will become crucial for applications requiring real-time responses, such as IoT and autonomous vehicles.

The projected growth indicates a strong and continuous demand for blockchain and cloud professionals in Europe and worldwide. As we stand at the “crossroads of infinity,” there is a significant skill shortage, which will likely increase with the rapid adoption of these technologies. A 2023 study by SoftwareOne found that 95% of businesses globally face a cloud skills gap. Specific skills in high demand include cloud security, cloud-native development, and expertise in leading cloud platforms like AWS, Azure, and Google Cloud. The European Commission’s Digital Economy and Society Index (DESI) highlights a need for improved digital skills in areas like blockchain to support the EU’s digital transformation goals. A 2023 report by CasperLabs found that 90% of businesses in the US, UK, and China adopt blockchain, but knowledge gaps and interoperability challenges persist.

The Role of Educational Institutions

This surge in demand necessitates a corresponding increase in qualified individuals who can design, implement, and manage cloud-based and blockchain solutions. Educational institutions have a critical role to play in bridging this widening skills gap and ensuring a pipeline of talent ready to meet the demands of this burgeoning industry.

To effectively prepare the next generation of cloud computing and blockchain experts, educational institutions need to adopt a multi-pronged approach. This includes enhancing curricula with specialized programs, integrating cloud and blockchain concepts into existing courses, and providing hands-on experience with leading technology platforms.

Furthermore, investing in faculty development to ensure they possess up-to-date knowledge and expertise is crucial. Collaboration with industry partners through internships, co-teach programs, joint research projects, and mentorship programs can provide students with invaluable real-world experience and insights.

Beyond formal education, fostering a culture of lifelong learning is essential. Offering continuing education courses, boot camps, and online resources enables professionals to upskill or reskill and stay abreast of the latest advancements in cloud computing. Actively promoting awareness of career paths and opportunities in this field and facilitating connections with potential employers can empower students to thrive in the dynamic and evolving landscape of cloud computing and blockchain technologies.

By taking these steps, educational institutions can effectively prepare the young generation to fill the skills gap and thrive in the rapidly evolving world of cloud computing and blockchain.

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