Artificial intelligence (AI) is a modern-day monolith that is likely going to be as important to the world as the introduction of the internet. We already see it creeping into every aspect of industry, from the basic chatbots you find on many websites to the self-driving cars under production at companies like Tesla.
As an industry, AI looks set to zoom past its current global valuation of $100 billion, becoming worth a staggering $2 trillion by 2030. To ensure you enjoy a prosperous career in an increasingly computer-powered world, you need to learn about AI. That’s where each artificial intelligence tutorial in this list can help you.
Top AI Tutorials for Beginners
If you know nothing about AI beyond the name, these are the three tutorials to get you started with the subject.
Tutorial 1 – Artificial Intelligence Tutorial for Beginners: Learn the Basics of AI (Guru99)
You need to get to the grips with AI theory before you can start with more practical work. Guru99’s tutorial helps you there, with a set of 11 lessons that take you from the most basic of concepts (what is AI?) to digging into the various types of machine learning. It’s like a crib notes version of an AI book, as it takes you on a speedy flight through AI fundamentals before capping its offer with a look at some practical applications.
Key Topics
- The basic theory of AI and machine learning
- Different types of machine learning algorithms
- An introduction to neural networking
Why Take This Artificial Intelligence Tutorial?
The tutorial is completely free, with every lesson being accessible via the Guru99 website with the click of a mouse. It’s also a great choice for complete AI newbies. You’ll cover the basics first, getting a grounding in AI in the process, before moving on to more complicated aspects of machine learning.
Tutorial 2 – Artificial Intelligence Tutorial for Beginners (Simplilearn)
This 14-lesson tutorial may seem intimidating at first. However, those 14 lessons only take an hour to complete, and the course has no prerequisites. This combination of brevity and a lack of tutorial requirements make it ideal for beginners who want to get to grips with the theory of AI. It’ll also help you develop some programming skills useful in more advanced courses.
Key Topics
- Basic programming skills you can use to develop AI models
- An introduction to Big Data and Spark
- Basic AI concepts, including machine learning, linear algebra, and algorithms
Why Take This Artificial Intelligence Tutorial?
Many of the tutorials you come across online will ask you to have a basic understanding of probability theory and linear algebra. This course equips you with those skills, in addition to giving you a solid grounding in many of the AI concepts (and machine learning models) you’ll encounter when you reach the intermediate level. Think of it as a crash course in the basics of AI.
Top AI Tutorials for Intermediate Learners
If you have a grasp of the basics, meaning you can separate your supervised learning algorithms from your unsupervised ones, you’re ready for these intermediate-level tutorials.
Tutorial 1 – Intro to Artificial Intelligence (Udacity)
Don’t let the use of the word “intro” in this tutorial’s name fool you because this is more than a mere explanation of AI concepts. As a four-month course, it requires you to have a good understanding of concepts like linear algebra and probability theory. Assuming you have that understanding, you’ll embark on a four-month self-paced learning journey (that’s completely free) that delves deep into the applications of AI.
Key Topics
- The theoretical and practical applications of natural language processing
- How AI has uses in every aspect of modern life, from advanced research to gaming
- The fundamentals of AI that underpin the practical applications you learn about
Why Take This Artificial Intelligence Tutorial?
The price tag is right, as this is one of the few Udacity courses you can take without spending any money. It’s also created by two of the best minds in AI – Peter Norvig and Sebastian Thrun – who deliver a nice mix of content, including instructor-led videos, quizzes, and experiential learning. Granted, there’s a large time commitment. But that commitment pays off as the course delivers a solid understanding of AI’s fundamentals and practical applications.
Tutorial 2 – Natural Language Processing Specialization (Coursera)
Anybody who’s used ChatGPT or “spoken” to a chatbot knows that a lot of companies are interested in what AI can do to deliver written content. That’s where Natural Language Processing (NLP) comes in, and this course is ideal for understanding the techniques that allow you to build chatbots and similar technologies.
Key Topics
- How to use logistic regression (and other techniques) to conduct sentiment analysis
- Build autocomplete and autocorrect models
- Discover how to develop AI algorithms that both detect and use human language
Why Take This Artificial Intelligence Tutorial?
Specialization is the key as you get deeper into the AI field. With this course, you focus your learning on language models and NLP, allowing you to dig deeper into an in-demand field that offers plenty of career opportunities. It’s somewhat intensive, requiring four months of study at about 10 hours per week to complete. But you get a shareable certificate at the end and develop a foundation in NLP that can apply in many business areas.
Top AI Tutorials for Advanced Learners
By the time you reach the advanced stage, you’re ready for your AI tutorials to teach you how to build and operate your own AI.
Tutorial 1 – Artificial Intelligence A-Z 2023: Build an AI With ChatGPT4 (Udemy)
With backing from a successful Kickstarter campaign, the Artificial Intelligence A-Z tutorial covers some of the fundamentals but focuses mostly on practical applications. You’ll create several types of AI, including a snazzy virtual self-driving car and an AI designed to beat simple games, helping you get to grips with how to put the theory you’ve learned into practice. The tutorial comes with 17 videos, a trio of downloadable resources, and 20 articles. All of which you can access whenever you need them.
Key Topics
- How to build practical AIs that actually do things
- The fundamentals of complex topics, such as Q-Learning
- How Asynchronous Advantage Actor Critic (AC3) applies to modern AI
Why Take This Artificial Intelligence Tutorial?
The two main reasons to take this tutorial are that it gives you hands-on experience with some exciting AI concepts, and you get a certificate you can put on your CV when you’ve finished. It’s well-structured and popular, with almost 204,000 students having already taken it from all over the world. And at just £59.99 (approx. €69), you get a lot of bang for your buck with videos, articles, and downloadable resources.
Tutorial 2 – A* Pathfinding Tutorial – Unity (YouTube)
Many prospective game developers will get their start with Unity, which is a free development tool that you can use to create surprisingly complex games. This YouTube tutorial series includes 10 videos, which walk you through how to use the A* algorithm to program AIs to determine the paths characters follow in a video game. It requires some programming knowledge, specifically C#, but it’s ideal for those who want to use their AI skills to transition into the world of gaming.
Key Topics
- Using the A* algorithm to create paths for AI-driven characters in video games
- Movement smoothing and terrain-related penalties
- Using multi-threading to improve pathfinding performance
Why Take This Artificial Intelligence Tutorial?
The price is certainly right for this tutorial, as the course creator (Sebastian Lague) makes all of his videos free to view on YouTube. But the biggest benefit of this tutorial is that it introduces complicated concepts that game developers use to determine character movement. If you’re interested in what makes video game characters “work” in terms of their actions in a game, this tutorial shows you the algorithm that underpins it all.
Additional AI Resources
The six tutorials in this list run the gamut from introducing you to the basics of AI to demonstrating specialized applications of the technology. Building on that knowledge requires you to go further, with the following books, podcasts, and websites all being great resources.
Great AI-Related Books
- Artificial Intelligence: A Modern Approach (Peter Norvig and Stuart Russell)
- Python: Advanced Guide to Artificial Intelligence (Giuseppe Bonaccorso)
- Neural Networks and Deep Learning (Charu C Aggarwal)
Great AI-Related Podcasts
- The AI Podcast (Noah Kravitz)
- Artificial Intelligence: AI Podcast (Lex Fridman)
- Eye on AI (Craig Smith)
Great AI-Related Websites and Blogs
- MIT News
- Analytics Vidhya
- KDnuggets
Understand Complex Concepts With an Artificial Intelligence Tutorial
AI is one of the world’s fastest-growing industries, with the previously-mentioned $2 trillion 2030 valuation representing a 20-fold growth from today. The point? Getting in close to the ground floor now by developing your understanding of AI concepts will set you up for a future in which many of the best jobs are in the AI field.
Each artificial intelligence tutorial in this list offers something different to students, from beginners who want to get to grips with AI to those who have a decent understanding and are ready to specialize. Regardless of the course you choose, the most important thing is that you keep learning. AI won’t stay static. It’s like a runaway locomotive that’s going to keep plowing forward, with nothing to stop it, to its next evolution. Use these tutorials to learn both basic and advanced concepts, then build on that learning with continued education.
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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