Machines that can learn on their own have been a sci-fi dream for decades. Lately, that dream seems to be coming true thanks to advances in AI, machine learning, deep learning, and other cutting-edge technologies.
Have you used Google’s search engine recently or admired the capabilities of ChatGPT? That means you’ve seen machine learning in action. Besides those renowned apps, the technology is widespread across many industries, so much so that machine learning experts are in increasingly high demand worldwide.
Chances are there’s never been a better time to get involved in the IT industry than today. This is especially true if you enter the market as a machine learning specialist. Fortunately, getting proficient in this field no longer requires enlisting in a college – now you can finish a Master in machine learning online.
Let’s look at the best online Masters in machine learning and data science that you can start from the comfort of your home.
Top MSc Programs in Machine Learning Online
Finding the best MSc machine learning online programs required us to apply certain strict criteria in the search process. The following is a list of programs that passed our research with flying colors. But first, here’s what we looked for in machine learning MSc courses.
Our Criteria
The criteria we applied include:
- The quality and reputation of the institution providing the course
- International degree recognition
- Program structure and curriculum
- Duration
- Pricing
Luckily, numerous world-class universities and organizations have a machine learning MSc online. Their degrees are accepted around the world, and their curricula count among the finest in the market. Take a look at our selection.
Imperial College London – Machine Learning and Data Science
The Machine Learning and Data Science postgraduate program from the Imperial College in London provides comprehensive courses on models applicable to real-life scenarios. The program features hands-on projects and lessons in deep learning, data processing, analytics, and machine learning ethics.
The complete program is online-based and relies mostly on independent study. The curriculum consists of 13 modules. With a part-time commitment, this program will last for two years. The fee is the same for domestic and overseas students: £16,200
European School of Data Science & Technology – MSc Artificial Intelligence and Machine Learning
If you need a Master’s program that combines the best of AI and machine learning, the European School of Data Science & Technology has an excellent offer. The MSc Artificial Intelligence and Machine Learning program provides a sound foundation of the essential concepts in both disciplines.
During the courses, you’ll examine the details of reinforcement learning, search algorithms, optimization, clustering, and more. You’ll also get the opportunity to work with machine learning in the R language environment.
The program lasts for 18 months and is entirely online. Applicants must cover a registration fee of €1500 plus monthly fees of €490.
European University Cyprus – Artificial Intelligence Master
The European University in Cyprus is an award-winning institution that excels in student services and engagement, as well as online learning. The Artificial Intelligence Master program from this university treats artificial intelligence in a broader sense. However, machine learning is a considerable part of the curriculum, being taught alongside NLP, robotics, and big data.
The official site of the European University Cyprus states the price for all computer science Master’s degrees at €8,460. However, it’s worth noting that there’s a program for financial support and scholarships. The duration of the program is 18 months, after which you’ll get an MSc in artificial intelligence.
Udacity – Computer Vision Nanodegree
Udacity has profiled itself as a leading learning platform. Its Nanodegree programs provide detailed knowledge on numerous subjects, such as this Computer Vision Nanodegree. The course isn’t a genuine MSc program, but it offers specialization for a specific field of machine learning that may serve for career advancement.
This program includes lessons on the essentials of image processing and computer vision, deep learning, object tracking, and advanced computer vision applications. As with other Udacity courses, learners will enjoy support in real-time as well as career-specific services for professional development after finishing the course.
This Nanodegree has a flexible schedule, allowing you to set a personalized learning pace. The course lasts for three months and has a fee of €944. Scholarship options are also available for this program, and there are no limitations in terms of applying for the course or starting the program.
Lebanese American University – MS in Applied Artificial Intelligence
Lebanese American University curates the MS in Applied Artificial Intelligence study program, led by experienced faculty members. The course is completely online and focuses on practical applications of AI programming, machine learning, data learning, and data science. During the program, learners will have the opportunity to try out AI solutions for real-life issues.
This MS program has a duration of two years. During that time, you can take eight core courses and 10 elective courses, including subjects like Healthcare Analytics, Big Data Analytics, and AI for Biomedical Informatics.
The price of this program is €6,961 per year. It’s worth noting that there’s a set application deadline and starting date for the course. The first upcoming application date is in July, with the program starting in September.
Data Science Degrees: A Complementary Path
Machine learning can be viewed as a subcategory of data science. While the former focuses on methods of supervised and unsupervised AI learning, the latter is a broad field of research. Data science deals with everything from programming languages to AI development and robotics.
Naturally, there’s a considerable correlation between machine learning and data science. In fact, getting familiar with the principles of data science can be quite helpful when studying machine learning. That’s why we compiled a list of degree programs for data science that will complement your machine learning education perfectly.
Top Online Data Science Degree Programs
Purdue Global – Online Bachelor of Science Degree in Analytics
Data analytics represents one of the essential facets of data science. The Online Bachelor of Science Degree in Analytics program is an excellent choice to get familiar with data science skills. To that end, the program may complement your machine learning knowledge or serve as a starting point for a more focused pursuit of data science.
The curriculum includes nine different paths of professional specialization. Some of those concentrations include cloud computing, network administration, game development, and software development in various programming languages.
Studying full-time, you should be able to complete the program within four years. Each course has a limited term of 10 weeks. The program in total requires 180 credits, and the price of one credit is $371 or its equivalent in euros.
Berlin School of Business and Innovation – MSc Data Analytics
MSc Data Analytics is a postgraduate program from the Berlin School of Business and Innovation (BSBI). As an MSc curriculum, the program is relatively complex and demanding, but will be more than worthwhile for anyone wanting to gain a firm grasp of data analytics.
This is a traditional on-campus course that also has an online variant. The program focuses on data analysis and extraction and predictive modeling. While it could serve as a complementary degree to machine learning, it’s worth noting that this course may be the most useful for those pursuing a multidisciplinary approach.
This MSc course lasts for 18 months. Pricing differs between EU and non-EU students, with the former paying €8,000 and the latter €12,600.
Imperial College London – Machine Learning and Data Science
It’s apparent from the very name that this Imperial College London program represents an ideal mix. Machine Learning and Data Science combines the two disciplines, providing a thorough insight into their fundamentals and applications.
The two-year program is tailored for part-time learners. It consists of core modules like Programming for Data Science, Ethics in Data Science and Artificial Intelligence, Deep Learning, and Applicable Mathematics.
This British-based program costs £16,200 yearly, both for domestic and overseas students. Some of the methods include lectures, tutorials, exercises, and reading materials.
Thriving Career Opportunities With a Masters in Machine Learning Online
Jobs in machine learning require proper education. The chances of becoming a professional in the field without mastering the subject are small – the industry needs experts.
A Master’s degree in machine learning can open exciting and lucrative career paths. Some of the best careers in the field include:
- Data scientist
- Machine learning engineer
- Business intelligence developer
- NLP scientist
- Software engineer
- Machine learning designer
- Computational linguist
- Software developer
These professions pay quite well across the EU market. The median annual salary for a machine learning specialist is about €70,000 in Germany, €68,000 in the Netherlands, €46,000 in France, and €36,000 in Italy.
On the higher end, salaries in these countries can reach €98,000, €113,000, €72,000, and €65,000, respectively. To reach these more exclusive salaries, you’ll need to have a quality education in the field and a level of experience.
Become Proficient in Machine Learning Skills
Getting a Master’s degree in machine learning online is convenient, easily accessible, and represents a significant career milestone. With the pace at which the industry is growing today, it would be a wise choice.
Since the best programs offer a thorough education, great references, and a chance for networking, there’s no reason not to check out the courses on offer. Ideally, getting the degree could mark the start of a successful career in machine learning.
Related posts
Source:
- 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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Source:
- The European Business Review, Published on October 27th, 2024.
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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