

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.
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During the Open Institute of Technology’s (OPIT’s) 2025 Graduation Day, we conducted interviews with many recent graduates to understand why they chose OPIT, how they felt about the course, and what advice they might give to others considering studying at OPIT.
Karina is an experienced FinTech professional who is an experienced integration manager, ERP specialist, and business analyst. She was interested in learning AI applications to expand her career possibilities, and she chose OPIT’s MSc in Applied Data Science & AI.
In the interview, Karina discussed why she chose OPIT over other courses of study, the main challenges she faced when completing the course while working full-time, and the kind of support she received from OPIT and other students.
Why Study at OPIT?
Karina explained that she was interested in enhancing her AI skills to take advantage of a major emerging technology in the FinTech field. She said that she was looking for a course that was affordable and that she could manage alongside her current demanding job. Karina noted that she did not have the luxury to take time off to become a full-time student.
She was principally looking at courses in the United States and the United Kingdom. She found that comprehensive courses were expensive, costing upwards of $50,000, and did not always offer flexible study options. Meanwhile, flexible courses that she could complete while working offered excellent individual modules, but didn’t always add up to a coherent whole. This was something that set OPIT apart.
Karina admits that she was initially skeptical when she encountered OPIT because, at the time, it was still very new. OPIT only started offering courses in September 2023, so 2025 was the first cohort of graduates.
Nevertheless, Karina was interested in OPIT’s affordable study options and the flexibility of fully remote learning and part-time options. She said that when she looked into the course, she realized that it aligned very closely with what she was looking for.
In particular, Karina noted that she was always wary of further study because of the level of mathematics required in most computer science courses. She appreciated that OPIT’s course focused on understanding the underlying core principles and the potential applications, rather than the fine programming and mathematical details. This made the course more applicable to her professional life.
OPIT’s MSc in Applied Data Science & AI
The course Karina took was OPIT’s MSc in Applied Data Science & AI. It is a three- to four-term course (13 weeks), which can take between one and two years to complete, depending on the pace you choose and whether you choose the 90 or 120 ECTS option. As well as part-time, there are also regular and fast-track options.
The course is fully online and completed in English, with an accessible tuition fee of €2,250 per term, which is €6,750 for the 90 ECTS course and €9,000 for the 120 ECTS course. Payment plans are available as are scholarships, and discounts are available if you pay the full amount upfront.
It matches foundational tech modules with business application modules to build a strong foundation. It then ends with a term-long research project culminating in a thesis. Internships with industry partners are encouraged and facilitated by OPIT, or professionals can work on projects within their own companies.
Entry requirements include a bachelor’s degree or equivalency in any field, including non-tech fields, and English proficiency to a B2 level.
Faculty members include Pierluigi Casale, a former Data Science and AI Innovation Officer for the European Parliament and Principal Data Scientist at TomTom; Paco Awissi, former VP at PSL Group and an instructor at McGill University; and Marzi Bakhshandeh, a Senior Product Manager at ING.
Challenges and Support
Karina shared that her biggest challenge while studying at OPIT was time management and juggling the heavy learning schedule with her hectic job. She admitted that when balancing the two, there were times when her social life suffered, but it was doable. The key to her success was organization, time management, and the support of the rest of the cohort.
According to Karina, the cohort WhatsApp group was often a lifeline that helped keep her focused and optimistic during challenging times. Sharing challenges with others in the same boat and seeing the example of her peers often helped.
The OPIT Cohort
OPIT has a wide and varied cohort with over 300 students studying remotely from 78 countries around the world. Around 80% of OPIT’s students are already working professionals who are currently employed at top companies in a variety of industries. This includes global tech firms such as Accenture, Cisco, and Broadcom, FinTech companies like UBS, PwC, Deloitte, and the First Bank of Nigeria, and innovative startups and enterprises like Dynatrace, Leonardo, and the Pharo Foundation.
Study Methods
This cohort meets in OPIT’s online classrooms, powered by the Canvas Learning Management System (LMS). One of the world’s leading teaching and learning software, it acts as a virtual hub for all of OPIT’s academic activities, including live lectures and discussion boards. OPIT also uses the same portal to conduct continuous assessments and prepare students before final exams.
If you want to collaborate with other students, there is a collaboration tab where you can set up workrooms, and also an official Slack platform. Students tend to use WhatsApp for other informal communications.
If students need additional support, they can book an appointment with the course coordinator through Canvas to get advice on managing their workload and balancing their commitments. Students also get access to experienced career advisor Mike McCulloch, who can provide expert guidance.
A Supportive Environment
These services and resources create a supportive environment for OPIT students, which Karina says helped her throughout her course of study. Karina suggests organization and leaning into help from the community are the best ways to succeed when studying with OPIT.

In April 2025, Professor Francesco Derchi from the Open Institute of Technology (OPIT) and Chair of OPIT’s Digital Business programs entered the online classroom to talk about the current state of the Metaverse and what companies can do to engage with this technological shift. As an expert in digital marketing, he is well-placed to talk about how brands can leverage the Metaverse to further company goals.
Current State of the Metaverse
Francesco started by exploring what the Metaverse is and the rocky history of its development. Although many associate the term Metaverse with Mark Zuckerberg’s 2021 announcement of Meta’s pivot toward a virtual immersive experience co-created by users, the concept actually existed long before. In his 1992 novel Snow Crash, author Neal Stephenson described a very similar concept, with people using avatars to seamlessly step out of the real world and into a highly connected virtual world.
Zuckerberg’s announcement was not even the start of real Metaverse-like experiences. Released in 2003, Second Life is a virtual world in which multiple users come together and engage through avatars. Participation in Second Life peaked at about one million active users in 2007. Similarly, Minecraft, released in 2011, is a virtual world where users can explore and build, and it offers multiplayer options.
What set Zuckerberg’s vision apart from these earlier iterations is that he imagined a much broader virtual world, with almost limitless creation and interaction possibilities. However, this proved much more difficult in practice.
Both Meta and Microsoft started investing significantly in the Metaverse at around the same time, with Microsoft completing its acquisition of Activision Blizzard – a gaming company that creates virtual world games such as World of Warcraft – in 2023 and working with Epic Games to bring Fortnite to their Xbox cloud gaming platform.
But limited adoption of new Metaverse technology saw both Meta and Microsoft announce major layoffs and cutbacks on their Metaverse investments.
Open Garden Metaverse
One of the major issues for the big Metaverse vision is that it requires an open-garden Metaverse. Matthew Ball defined this kind of Metaverse in his 2022 book:
“A massively scaled and interoperable network of real-time rendered 3D virtual worlds that can be experienced synchronously and persistently by an effectively unlimited number of users with an individual sense of presence, and with continuity of data, such as identity, history, entitlements, objects, communication, and payments.”
This vision requires an open Metaverse, a virtual world beyond any single company’s walled garden that allows interaction across platforms. With the current technology and state of the market, this is believed to be at least 10 years away.
With that in mind, Zuckerberg and Meta have pivoted away from expanding their Metaverse towards delivering devices such as AI glasses with augmented reality capabilities and virtual reality headsets.
Nevertheless, the Metaverse is still expanding today, but within walled garden contexts. Francesco pointed to Pokémon Go and Roblox as examples of Metaverse-esque words with enormous engagement and popularity.
Brands Engaging with the Metaverse: Nike Case Study
What does that mean for brands? Should they ignore the Metaverse until it becomes a more realistic proposition, or should they be establishing their Meta presence now?
Francesco used Nike’s successful approach to Meta engagement to show how brands can leverage the Metaverse today.
He pointed out that this was a strategic move from Nike to protect their brand. As a cultural phenomenon, people will naturally bring their affinity with Nike into the virtual space with them. If Nike doesn’t constantly monitor that presence, they can lose control of it. Rather than see this as a threat, Nike identified it as an opportunity. As people engage more online, their virtual appearance can become even more important than their physical appearance. Therefore, there is a space for Nike to occupy in this virtual world as a cultural icon.
Nike chose an ad hoc approach, going to users where they are and providing experiences within popular existing platforms.
As more than 1.5 million people play Fortnite every day, Nike started there, first selling a variety of virtual shoes that users can buy to kit out their avatars.
Roblox similarly has around 380 million monthly active users, so Nike entered the space and created NIKELAND, a purpose-built virtual area that offers a unique brand experience in the virtual world. For example, during NBA All-Star Week, LeBron James visited NIKELAND, where he coached and engaged with players. During the FIFA World Cup, NIKELAND let users claim two free soccer jerseys to show support for their favorite teams. According to statistics published at the end of 2023, in less than two years, NIKELAND had more than 34.9 million visitors, with over 13.4 billion hours of engagement and $185 million in NFT (non-fungible tokens or unique digital assets) sales.
Final Thoughts
Francesco concluded by discussing that while Nike has been successful in the Metaverse, this is not necessarily a success that will be simple for smaller brands to replicate. Nike was successful in the virtual world because they are a cultural phenomenon, and the Metaverse is a combination of technology and culture.
Therefore, brands today must decide how to engage with the current state of the Metaverse and prepare for its potential future expansion. Because existing Metaverses are walled gardens, brands also need to decide which Metaverses warrant investment or whether it is worth creating their own dedicated platforms. This all comes down to an appetite for risk.
Facing these types of challenges comes down to understanding the business potential of new technologies and making decisions based on risk and opportunity. OPIT’s BSc in Digital Business and MSc in Digital Business and Innovation help develop these skills, with Francesco also serving as program chair.
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