AI is everywhere today.

The algorithms that drive your Netflix and Spotify recommendations use AI to figure out what you’ll like based on what you’ve already consumed. Every chatbot you’ve ever spoken to, targeted ad you’ve seen, and even the more fanciful ideas floating around (self-driving cars, anyone?) use AI to some degree.

Given that so many businesses use AI already, it stands to reason that taking online courses on the subject will help you get ahead. But for the budget-conscious among you, a course that costs thousands of euros isn’t the route you want to go down. You want a free AI course.

That’s where this article comes in. But let’s get something clear immediately, a free AI course won’t go into as much depth as a paid one. Nor will it give you a qualification that’s as prestigious as one from a formal educational institution. But what it will give you is foundational knowledge, often backed by a certification, which is why we’re looking at four of the best AI courses you can study for free in this article.

Top Artificial Intelligence Course Online Free With Certificate – Four Great Options

Is it really possible to find an artificial intelligence free course with certificate that shows you have actually learned something useful? It is, and these four courses are great examples.

Course 1 – Elements of AI (University of Helsinki)

With over 950,000 students already to its name, the Elements of AI course is all about lifting the veil on the mysterious concept of AI. It includes two modules, the first giving you an introduction to the “whats” and “wherefores” of AI, with the second digging into building your own AI models. It’s set up to run in 170 countries and is ideal for those who want a basic grasp on AI that they can build on with other courses.

Key Topics Covered

  • The theory of AI, including what is and isn’t possible with the tech
  • Development of basic AI algorithms
  • An introduction (and exploration) of using Python to create AI models
  • Practical exercises that you can take at your own pace to see how AI applies in real-world scenarios

Certificate Details

The certification you get from this free AI course comes directly from the University of Helsinki, which is a recognized and authoritative European institution. But it’s important to note that the certificate is not a degree. Instead, it’s both a demonstration of your grasp of basic AI concepts and a statement of your intent to dig deeper into the topic.

Course 2 – Machine Learning With Python: A Practical Introduction (IBM)

There are three things you want from your AI course – online, free, and practical. IBM’s offering delivers all three, with the focus being on how you can apply machine learning (with Python programs underpinning your models) to the real world. The content is created and delivered by Saeed Aghabozorgi, who’s a senior data scientist at IBM, meaning it comes direct from somebody who understands precisely how machine learning is applied in practical terms.

Key Topics Covered

  • Python programming in the context of creating machine learning models
  • The theory and application of both supervised and unsupervised learning
  • An introduction to the most common machine learning algorithms
  • Real-world examples of how machine learning is already impacting society

Certificate Details

In return for five weeks of your time (estimated study – four to five hours per week) you’ll earn an IBM “skill badge.” This online credential verifies that you’ve completed the course and can be shared on social media profiles. The course is also part of IBM’s Data Science Professional Certificate Program, making it a piece of a larger jigsaw puzzle of free AI courses that you can complete over the course of a year to get an IBM certificate.

Course 3 – Supervised Machine Learning: Regression and Classification (DeepLearning.AI via Coursera)

You’re getting into specialization territory with this course, which serves as the first of several that make up DeepLearning.AI’s Machine Learning Specialization certificate. It’s a completely online course that allows you to reset deadlines to suit your schedule and takes about 33 hours of studying to complete. Sadly, it’s only available in English (at the time of writing), which may make it less accessible to non-English speakers.

Key Topics Covered

  • A wide-spanning introduction to the various types of machine learning
  • Explanations of the best practices for AI implementation currently used in major Silicon Valley companies
  • Several mathematical and statistical concepts, such as linear regression
  • Practical examples and project work for building predictive machine learning models

Certificate Details

Coursera provides its own shareable certificates to anybody who completes this course, with those certificates being shareable on social media and printable for your CV. It’s also worth noting that this course is part of a wider three-course program. Combine it with DeepLearning.AI’s Advanced Learning Algorithms and Unsupervised Learning and Recommender Systems to get two more course-specific certificates and a certificate for completing all three courses.

Course 4 – Learn With Google AI (Google)

Learn with Google AI is less a dedicated course and more a collection of different modules (and even competitions) designed to help you get to grips with AI. Think of it like a resource bank, only it incorporates practical exercises as well as theoretical information. Beyond the courses themselves, you’ll find a useful glossary and some guides for how AI can apply to environmental and social courses.

Key Topics Covered

  • Theoretical modules covering machine learning, neural networks, and the ethics behind AI
  • Hands-on tutorials that give you practical experience with the course content
  • Real-world examples of how Google incorporates AI into what it does
  • Competitions that allow you to test your skills against other participants

Certificate Details

Learn with Google AI isn’t a traditionally structured course, and that’s reflected in the lack of certification for completing the courses in this resource bank. It’s better to think of these courses as free primers that equip you with the knowledge you need to ace other free (or paid) AI courses.

Factors to Consider When Choosing an AI Course

The price is certainly right with a free AI course, but you’re still investing valuable time into whichever program you choose. Think about the following to ensure you spend that time wisely:

  • Course content – Though many artificial intelligence free course will cover the basic concepts underpinning AI, you want to know that you’re going somewhere with what you learn. Think about why you’re studying AI and whether the course will move you closer to your goals.
  • Course duration and flexibility – Online courses come with a key advantage over traditional programs – you control your studying. That flexibility allows you to fit your studies around your life, though you still have deliverables (and sometimes tests) you need to complete.
  • Instructor credentials – With free courses, the certification you get isn’t as immediately prestigious as one you’d receive from a paid course. A respected instructor can add that prestige. Research the background of whoever creates and delivers the course, specifically checking their reputation as a teacher and experiences in the AI industry.
  • Community support and resources – Given that most free AI courses focus on self-learning, you need to know that there are people (or resources) around to help when you get stuck. No learner is an island. If there are other students and instructors around to offer guidance, you have a course that you’re more likely to pass.
  • Certificate value – As touched upon earlier, the value of your certificate plays a role in your decision, with specific attention being paid to how employers will see that certificate on your CV. A respected instructor or a course delivered by a major brand (think Google or IBM) adds credibility compared to courses delivered by nameless and faceless individuals.

Tips for Successfully Completing an AI Course Online

No athlete gets a gold medal for running half a race, and the same applies to students who don’t complete the courses they start. Use these tips to see you through when the going gets tough:

  • Set clear goals for yourself, which inform the course you choose and help to motivate you if you start feeling discouraged when struggling with the material.
  • Dedicate time to learning both in the context of your course and by parsing out personal time for practice.
  • Engage with the community that’s evolved around the course to learn directly from peers and qualified professionals.
  • Never be afraid of seeking help when needed, as you’re learning some complex concepts that are all too easy to misinterpret.
  • Take every opportunity you can find to apply the theoretical concepts you learn in real-world scenarios.

Study AI Courses Free Online

A free AI course is never going to be a direct substitute for a paid course delivered by a recognized institution. But it doesn’t have to be. Free courses can set you up with general skills that you can apply in your existing workplace, in addition to helping you lay a foundation for future study. And in some cases (such as with courses offered directly by major AI players) you’ll get a certification that actually means something to employers.

AI is going to be so much more than a part of future technology. It’ll be the bedrock on which everything to come is built. Your efforts to expand your knowledge in the field will help you become one of the people who lay that bedrock. The sooner you start learning (and applying) AI, the better your position will be when the AI revolution truly takes hold.

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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
OPIT - Open Institute of Technology
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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