Artificial intelligence (AI) permeates every aspect of modern society, with that effect only becoming more pronounced as we move deeper into the 21st century. That’s a statement supported by the Brookings Institute, which asserts that whoever rules AI by 2030 (be it a country or corporation) will rule the global roost until at least 2100.

The point is that AI is already everywhere, even if in limited capacities, and you need to be ready for an AI-centric world to unfold ahead of you in the future. The right AI courses ensure you’re ready, so let’s look at four that you can complete today.

What Is Artificial Intelligence (AI)?

As humans, our brains give us the ability to learn and adapt to everything around us. For computers, AI achieves the same thing, equipping machines with the ability to take in datasets, learn from the data, and apply what it learns to real-world scenarios. There are many types of AI, with the following three being among the most prominent:

  • Narrow AI – An AI system that’s dedicated to performing a single task, like a chatbot that delivers stock responses based on user queries. Think of these AI as the “manual labor” machines that exist to do the same thing over and over again.
  • General AI – With general AI, we move closer to AI that has the same capacities to learn and apply that humans have. Multi-functional is the keyword here, as these AIs will be capable of completing multiple tasks at a human level.
  • Superintelligent AI – Though not in existence yet, superintelligent AI is the pinnacle of AI research, or the peak on the Mount Everest of AI. In addition to bringing the multi-functional talents that humans have to the table, these AI will have an unlimited capacity for learning.

We’re nowhere near the superintelligent AI level yet (some even say that this type of AI will be more of a threat than a help to humanity), but we can see AI in so many industries already. Self-driving cars, automated stock checkers, and even email spam filters are all examples of narrow AI in action, with each having specific functions. As the technology evolves, and it’s already doing so at a rapid pace, we’ll see more multi-function AI come to the fore.

Factors to Consider When Choosing an AI Course

When choosing a course, the key question is always what is artificial intelligence course criteria that actually matters? Here are five things to look for in an artificial intelligence course:

  • Quality course content – In this context, “quality” doesn’t solely mean “good” (though that’s a part of it). Your course also needs to deliver an educational experience that furthers whatever goals you’ve set for yourself in your career.
  • Course flexibility – Some people can commit themselves fully to an AI course. Others need to fit their learning around work, family, and other commitments. Figure out which category you slot into and search for courses that offer the flexibility (or lack thereof) that you need.
  • Instructor expertise – Good instructors bring a combination of theoretical mastery and industry experience to their courses. That’s why the best AI courses are usually created, and run, by people who currently work in the field.
  • Course reviews and ratings – Online reviews and ratings are the modern “word of mouth,” with global courses benefitting (or otherwise) from what their students have to say online. A few minutes of research can tell you if other students consider your chosen course to be a dud or an AI masterclass.
  • Pricing – As attractive as a full Master’s degree may be, the five-figure pricing may feel prohibitive. Other courses, such as a short-term artificial intelligence online course, may offer snippets of what you need to know at a much lower price. Balance your needs against your budget to make your choice.

Top AI Online Courses

There is no such thing as the “best” artificial intelligence course because every course offers something different that may or may not align with your needs. But these four run the gamut, from full-blown Master’s degrees (with accreditation) to crash courses designed to get you up to speed as fast as possible.

Course 1 – CS50’s Introduction to Artificial Intelligence With Python (Harvard)

There are few educational institutions as prestigious as Harvard University, and its CS50 course is perfect for those who already have a grasp of the Python programming language. Offered completely online, it’s a self-paced course that comes with a verified certificate (assuming you’re willing to pay an extra $199/€180).

Key Topics Covered

  • Reinforcement learning as it applies to machine learning
  • The core principles of artificial intelligence
  • Creating Python programs that use AI
  • An in-depth study into graph search algorithms

Course Duration and Pricing

Harvard advertises the course as a seven-week-long self-paced online program and recommends between 10 and 30 hours of study per week. How much time you actually spend on your studies depends on how quickly you pick up the concepts. It’s free to enroll (though a certificate costs money, as mentioned) and enrollment is open between May and December of each year.

Course 2 – Expand Your Knowledge of Artificial Intelligence (Udacity)

Marketed as a “nanodegree” program, which basically means it packs a lot of information into a short timeframe. Expand Your Knowledge gives you access to a digital classroom. It comes with some prerequisites, such as an understanding of Python and statistics, but it’s a course designed for those taking their first steps into applied AI.

Key Topics Covered

  • Foundational AI algorithms that power things like NASA’s Mars Rover
  • An introduction to AI concepts using Python as your base programming language
  • Classical graph search algorithms
  • Project reviews and feedback from over 1,400 people in the AI field

Course Duration and Pricing

This is a three-month course, with estimated study hours of between 12 and 15 per week, making it ideal for part-time learners who want to grasp the fundamentals of AI. Pricing is flexible, too. You can subscribe to the monthly version of the course via Udacity at a cost of £329 (approx. €377) per month or buy the whole thing upfront for £837 (approx. €959).

Course 3 – Master in Applied Data Science & AI (OPIT)

Those who’ve already completed a Bachelor’s degree in a computing or statistical subject may want to continue their full-time studies. OPIT’s Master’s program offers that opportunity, with its 100% online course being supported by experienced tutors who are available literally whenever you need them. The course contains both live and prerecorded content and the degree you receive carries European Qualification Framework accreditation.

Key Topics Covered

  • Real-life business problems (and solutions) that use both AI and data science
  • Python programming in the context of AI and data science
  • Business-related topics, such as the ethics surrounding AI usage and project management
  • Applied machine learning and artificial intelligence techniques

Course Duration and Pricing

OPIT’s Master’s program is a full-time postgraduate course. The regular version takes 18 months of self-timed study to complete. A fast-track version is available, lasting for 12 months, for those who want a more intensive educational experience. The cost varies depending on when you enroll. Intakes occur in October of each year, with early birds paying a discounted price of €4,950, to save almost €1,500 on the usual €6,500 price.

Course 4 – AI Engineering Professional Certificate (IBM via Coursera)

For those looking for direct tutelage from professionals who already work in the AI field, IBM’s offering is one of the best AI courses online. It’s also ideal for beginners, with no experience in computing needed and a flexible schedule allows you to learn as and how you want. Those studying for formal degrees aren’t left out. The certificate you earn through this course counts toward your degree credit.

Key Topics Covered

  • The foundations of machine learning and neural networks
  • Machine learning algorithm deployment
  • Neural network development using PyTorch, Keras, and TensorFlow
  • Implementation of both supervised and unsupervised machine learning models

Course Duration and Pricing

Flexibility is the name of the game with this course. It lasts for eight months, with three hours of learning per week, though fast and full-time learners may be able to complete it much quicker. Enrollment begins in May of each year, and the first seven days of the course act as a free trial so you can get a taste of what it has to offer. It’s also fairly cheap, with the course costing around €125 if you go for the full eight-month option.

Benefits of Taking AI Courses

There’s no use looking for the best artificial intelligence course if you don’t understand how that course will help you in the future. These are four benefits of studying AI:

  • Develop a skillset that will not only be important as we move toward an AI-driven future, but will serve as a foundation for the skills you’ll need to develop as AI evolves.
  • Combine theoretical and practical knowledge of AI to make your CV sparkle when it’s in front of employers.
  • Create the problem-solving skills that are essential in the tech industry, with those skills often being transferable to other sectors.
  • Follow whatever path you want in the constantly branching AI field.

Take Your Next Career Step With an Artificial Intelligence Online Course

Each of the four courses highlighted here offers something different. Some are short-term introductory courses while others allow full-time students to continue in-depth formal education. Whichever you choose serves as an investment into your future. AI is already causing ripples in the industrial ocean, and those ripples will grow into a tidal wave of opportunity for those who are prepared for the explosive growth of the industry. By investing in yourself today, through education and career foresight, you set yourself up for an amazing future tomorrow.

Related posts

Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 14, 2025 6 min read

Source:


Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

Read the full article below (in Italian):

Read the article
The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 10, 2025 7 min read

There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

  • Where we are currently with AI and future trajectories
  • The impact AI is having on the job landscape
  • Sustainability concerns and ethical dilemmas
  • The fundamental risks associated with current AI technology

According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

  • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
  • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
  • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
  • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
  • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
  • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

Read the article