Artificial Intelligence (AI) and machine learning are two of the fastest-growing emerging technologies right now. In late 2022, generative AI burst onto the tech scene in the shape of ChatGPT and its antecedents. However, that’s not the first time AI has made a major impact. In fact, the first AI chatbot, Eliza, was around in the 1960s.
Both AI and machine learning do far more than chat and research. AI is embedded in analytics, predictive forecasting, and monitoring for multiple industries. As the use of AI and machine learning expands, the need for professionals with relevant skills is also growing exponentially.
OPIT (Open Institute of Technology) provides top-tier education in various tech fields, including highly respected machine learning and artificial intelligence courses. Let’s take a look at these fascinating technologies and how the right AI machine learning course can elevate your tech career.
Understanding AI and Machine Learning
When you’re searching for courses on artificial intelligence and machine learning, it helps to have a basic definition for both terms. If you already work in the tech industry, you likely work with one or both of these technologies every day. Yet they’re often so embedded within systems or apps that you might not even realize.
AI refers to the computer’s to exhibit behavior that replicates human thought patterns. However, the details of this definition are a little more complex than that. “Computers” can mean anything from a small subsystem to a supercomputer. It can also mean your smartphone or an app. And, by emulating human behavior, experts don’t necessarily mean AI does things exactly like us. Truly “thinking” AI with genuine cognitive abilities is a long way off.
What AI actually does is take things humans can already do – and do it faster and more often. Think about a software DevOps team requiring automated monitoring and testing of code prior to deployment. AI can do this while checking for vulnerabilities and producing relevant, actionable reports. In healthcare, AI uses pattern recognition to diagnose diseases quickly.
Machine learning is a subset of AI. It focuses on using algorithms to consistently and continuously improve pattern recognition for AI that appears to “learn.”
Courses in AI and machine learning are so popular because of the inherent usefulness of these technologies. Learning these skills now is a way to future-proof your tech career.
The Best AI and Machine Learning Courses
Numerous artificial intelligence and machine learning courses cover different topics and niches. You may choose to learn in a classroom setting or remotely. Some courses are short-term, generally covering foundational aspects of AI. Others carry on over several months for a deeper learning experience. Always consider how the course you invest in will impact your career advancement opportunities.
Absolute beginners may benefit from the Coursera IBM Applied Professional Certificate. This course runs entirely online over three months, presuming you can commit to 10 hours a week. Students learn the basics of AI, particularly how it powers IBM’s Watson AI services.
Oxford Online runs a 6-week online AI program course requiring 7-10 hours of commitment a week. This course looks at AI concepts and business cases for implementation and takes a glimpse at the future of AI.
For classroom-based courses on AI and machine learning, prospective students are best placed to contact local educational institutions. Offline courses vary in length, depth, and usefulness, so always check the syllabus and what certification you gain. It’s worth considering how far you’ll have to travel to gain a qualification.
One of the biggest challenges with AI is making it ethical. OPIT addresses that head-on with the MSc in Responsible AI. Learn advanced AI skills while keeping inclusivity and human interest at the heart of every aspect of the syllabus.
OPIT also offers other courses that consider the impact AI has on modern business practice. Undergraduates could consider the BSc in Digital Business, which includes a full Introduction to AI segment. There are also elective topics, including AI-Driven Software Development.
The Structure of AI and Machine Learning Courses
What should you expect from the best courses on AI and machine learning? Each course has a specific length, either in terms of study hours or a set deadline date. Most online courses have a specific intake date to make sure students get the right support at the right time.
Once you start your machine learning and AI course, you can expect a good balance between theory and practical application. For example, OPIT’s master’s degree course starts with foundational theory and critical thinking around ethics in AI. From here, students get to handle complex data sets. They program in Python and learn how to design effective AI-powered data pipelines.
The structure of your course will depend on the focus, but to give you the best foundation, courses may follow a similar pathway to this:
- Basics of AI, including the differences between AI and machine learning
- Discovering applications of AI — these may be general or industry-specific, depending on the nature of your course
- Data collation, analysis, and visualization
- Programming for AI
- Natural language processing (NLP) and natural language generation (NLG)
- Removing or preventing bias in AI training
Some courses will also offer advanced elective programs, such as understanding AI within the sphere of FinOps (financial operations) or business strategy. If you have a particular industry you’re hoping to excel in, look out for courses with topics that could help you further those ambitions.
Online AI and Machine Learning Courses: Flexibility and Accessibility
Choosing one of the best machine learning and AI courses to do online offers more benefits than new skills. Online learning allows you to study in your preferred environment and at your own pace. You just need to make sure you keep an eye on set deadlines.
You’re not distracted by a class full of people, but you still have access to tutors and support. Many open learning institutes have online communities of students. These are great for preventing isolation and gaining advice.
As a tech professional, the ability to set your own study schedule is essential. Online AI and machine learning courses provide flexibility, allowing you to learn as you work. With OPIT’s Master’s Degree in Responsible Artificial Intelligence, you could potentially have an MSc in 12-18 months without taking any time off work.
Key Skills Gained from AI and Machine Learning Courses
When choosing your online course on AI and machine learning, consider the skills you’ll learn. You should expect to cover:
- Data preprocessing
- Data cleansing
- Data visualization and storytelling
- Linear and nonlinear dimensionality reduction
- Manifold learning
- Human-centered AI design
- Language-agnostic AI programming skills
An MSc in AI and machine learning provides specialized skills and knowledge that you can use to address complex AI challenges in just about any industry.
Choosing the Right AI and Machine Learning Course for You
Picking the right AI and machine learning course is simpler when you consider your goals. Do you want a quick upskill and insight into emerging technologies? Or do you want an immersive course that empowers you to take on new career challenges? Most AI and machine learning courses will provide guidance on the type of career students could hope to pursue after completion.
Always look at the syllabus of a course and see if it meets your personal goals. If you’re unsure about any aspects, contact the education provider for more information.
OPIT’S MSc in Responsible Artificial Intelligence: An Overview
If you’ve decided an online AI and machine learning course is for you, as a graduate, an MSc is the natural choice. The next intake for the OPIT MSc in Responsible AI is September 2024, and details on how to apply are online.
What are the benefits of taking this course?
- A fast-track option to gain your master’s degree in just 12 months
- Fully inclusive fees — no hidden charges
- Various scholarship and funding options
- Availability of early-bird discounts
- Access to academic leaders from all over the world
- Education with an EU-accredited institution
Your MSc course covers every aspect of AI you might require for a career in AI and machine learning. Topics start with AI and ethics and quickly move into human-centered design, computer vision, and how AI impacts IoT and automation.
As you move into your final term, you start your MSc thesis, which focuses on AI projects with industrial relevance. There’s also the opportunity to pursue an internship to complement your thesis and gain vital experience.
AI and Machine Learning Courses for a Future-Proof Career
AI is now part of most growing industries, from property and real estate to healthcare and social care. Tech professionals have the opportunity to upskill themselves and move into fields that they have a real passion for. Organizations are looking for and willing to pay high salaries for knowledgeable, qualified AI experts.
Taking the time now to embark on machine learning and AI courses could speed your journey along your chosen career trajectory.
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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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