AI is already a massive industry – valued at $136.55 billion (approx. €124.82 billion) as of 2022 – and it’s only going to get bigger as we come to grips with what AI can do. As a student, you stand on the cusp of the AI tidal wave and you have an opportunity to ride that wave into a decades-long career.


But you need a starting point for that career – a BSc computer science with artificial intelligence. The three courses discussed in this article are the best for budding AI masters.


Factors to Consider When Choosing a BSc Computer Science With AI Program


Before choosing your BSc, you need to know what to look for in a good course:


  • Institution Accreditation – Whoever provides the course should offer solid accreditation so that you know you can trust the institution and that potential future employers actually respect the qualification you have on your VC.
  • An AI-Focused Curriculum – Not all computer science bachelor’s degrees are the same. The one you choose needs to offer a specific focus on AI or machine learning so you can build the foundations for later specialization.
  • Faculty Expertise – A course led by instructors who don’t know much about AI is like the blind leading the blind. Every mentor, instructor, and lecturer needs to have provable knowledge and industry experience.
  • Job Opportunities – Every chance you have to “get your hands dirty” with AI is going to look great on your CV. Look for courses that create pathways into internships and job programs. Associations with organizations like IBM are a great place to start.
  • Financial Aid – It isn’t cheap to study a BSc artificial intelligence and machine learning. Degrees cost thousands of Euros per year (the average in Europe is about €3,000, though prices can go higher) so the availability of financial aid is a huge help.

Top BSc Computer Science With AI Programs


Studying from the best is how you become a leader in the AI field. The combination of expert tuition and the name recognition that comes from having a degree from one of the following institutions stands you in good stead for success in the AI industry. Here are the top three organizations (with degrees available to overseas students) in the world.



Course 1 – BSc Artificial Intelligence – The University of Edinburgh


Named as one of the top 10 AI courses in the world by Forbes, The University of Edinburgh’s offering has everything you need from a great BSc computer science with artificial intelligence. It’s a four-year full-time course that focuses on the applications of AI in the modern world, with students developing the skills to build intelligent systems capable of making human-like decisions. The course is taught by the university’s School of Informatics, led by National Robotarium academic co-lead Professor Helen Hastie.


The course starts simple, with the first year dedicated to learning the language of computers before the second year introduces students to software development and data science concepts. By the third year, you’ll be digging deep into machine learning and robotics. That year also comes with opportunities to study abroad.


As for career prospects, The University of Edinburgh has a Careers Service department that can put you in line for internships at multi-national businesses. Add to that the university’s huge alumni network (essentially a huge group of professionals willing to help students with their careers) and this is a course that offers a great route into the industry.


Course 2 – Artificial Intelligence Program – Carnegie Mellon University


Ranked as the top university in the world for AI courses by Edurank, Carnegie Mellon University is a tough nut to crack if you want to study its world-renowned program. You’ll face a ton of competition, as evidenced by the university’s 17% acceptance rate, and the program is directed by Reid Simmons. For those who don’t recognize the name, he’s been a frontrunner in leveraging AI for NASA and was the creator of the “Robotceptionist.”


As for the course, it blends foundational mathematical, statistical, and computer science concepts with a wide variety of AI modules. It’s robotics-focused (that’s no surprise given the director), though you’ll also learn how AI applies on a perceptive level. The use of AI in speech processing, search engines, and even photography are just some examples of the concepts this course teaches.


Carnegie Mellon takes an interesting approach to internships, as it offers both career and academic internships. Career internships are what you’d expect – placements with major companies where you get to put your skills into practice. An academic internship is different because you’ll be based in the university and will work alongside its faculty on research projects.


Course 3 – BSc in Artificial Intelligence and Decision Making – Massachusetts Institute of Technology (MIT)


It should come as no surprise that MIT makes it onto the list given the school’s engineering and tech focus. Like Carnegie Mellon’s AI course, it’s tough to get into the MIT course (only a 7% acceptance rate) but simply having MIT on your CV makes you attractive to employers.


The course takes in multiple foundational topics, such as programming in Python and introductions to machine learning algorithms, before moving into a robotics focus in its application modules. But it’s the opportunities for research that make this one stand out. MIT has departments dedicated to the use of AI in society, healthcare, communications, and speech processing, making this course ideal for those who wish to pursue a specialization.


Networking opportunities abound, too. MIT’s AI faculty has 92 members, all with different types of expertise, who can guide you on your path and potentially introduce you to career opportunities. Combine that with the fact you’ll be working with some of the world’s best and brightest and you have a course that’s built for your success in the AI industry.


Emerging BSc Computer Science With AI programs


Given that AI is clearly going to be enormously important to developing industry in the coming years, it’s no surprise that many institutions are creating their own BSc computer science with artificial intelligence courses. In the UK alone, the likes of Queen’s University Belfast and Cardiff University are quickly catching up to The University of Edinburgh, especially in the robotics field.


In North America, the University of Toronto is making waves with a course that’s ranked the best in Canada and fifth in North America by EduRank. Interestingly, that course is a little easier to get into than many comparable North American courses, given its 43% acceptance rate.


Back in the UK, the University of Oxford is also doing well with AI, though its current courses tend to be shorter and specialized in areas like utilizing AI in business. We’re also seeing Asian universities make great progress with their courses, as both Tsinghua University and Nanyang Technological University are establishing themselves as leaders in the space.


Importance of Hands-On Experience and Internships


As important as foundational and theoretical knowledge is, it’s when you get hands-on that you start to understand how much of an impact AI will have on business and society at large. Good universities recognize this and offer hands-on experience (either via research or internship programs) that offer three core benefits:


  • Gain Practical Skills – Becoming a walking encyclopedia for the theory of AI is great if you intend on becoming a teacher. But for everybody else, working with hands-on practical experiments and examples is required to develop the practical skills that employers seek.
  • Networking – A strong faculty (ideally with industry as well as academic connections) will take you a long way in your BSc computer science with artificial intelligence. The more people you encounter, the more connections you build and the better your prospects are when you complete your course.
  • Enhanced Job Prospects – Getting hands-on with real-world examples, and having evidence of that work, shows employers that you know how to use the knowledge you have knocking around your head. The more practical a course gets, the better it enhances your job prospects.

Scholarships and Financial Aid Opportunities


Due to BSc artificial intelligence and machine learning courses being so expensive (remember – an average of €3,000 per year), financial aid is going to be important for many students. In the UK, that aid often comes in the form of student loans, which you don’t have to start repaying until you hit a certain earnings threshold.


When we take things Europe-wide, more scholarship and financial aid programs become available. The Erasmus program offers funding for master’s students (assuming they meet the criteria) and there are several scholarship portals, such as EURAXESS and Scholarshipportal designed to help with financial aid.


If this is something you’re interested in, the following tips may help you obtain funding:


  • Excel academically in pre-university studies to demonstrate your potential
  • Speak to the finance teams at your university of choice to see what’s currently available
  • Apply for as many scholarship and aid programs as you can to boost your chances of success

Try the Top BSc Artificial Intelligence and Machine Learning Programs


The three BSc computer science with artificial intelligence programs discussed in this article are among the best in the world for many reasons. They combine intelligence course focuses with faculty who not only know how to teach AI but have practical experience that helps you learn and can serve useful networking purposes.


The latter will prove increasingly important as the AI industry grows and becomes more competitive. But as with any form of education, your own needs are paramount. Choose the best course for your needs (whether it’s one from this list or an online BSc) and focus your efforts on becoming the best you can be.

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The Yuan: AI is childlike in its capabilities, so why do so many people fear it?
OPIT - Open Institute of Technology
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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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