It can often feel like a computer has a “brain,” especially given modern machines’ abilities to run complex calculations and handle instructions. But all of those machines need people behind them to program algorithms and help them to learn based on explicit instructions. That’s where machine learning comes in.

This branch of artificial intelligence brings a machine’s “brain” closer to the real thing than ever before. It’s all about teaching the machine how to do more than simply execute, as machine learning is all about making a machine “think” (based on instructions and algorithms) so it can improve over time. That ability to “think” is crucial in modern business because it gives companies the ability to analyze patterns – both operational and consumer-based – enabling them to make smarter decisions.

But these businesses need people who understand how to create machine learning models. That’s where you come in. With the right machine learning tutorial under your belt, you set yourself up for a career in a field that has only just started to show glimpses of its potential.

The Best Machine Learning Tutorials

Finding the best online tutorial for machine learning isn’t easy given the sheer volume of options available. Analyzing each one based on what it teaches (and how useful it will be to your career) takes time, though you can save yourself that time by checking out the three tutorials highlighted here.

Tutorial 1 – Intro to Machine Learning (Kaggle)

As tempting as it may be to run before you can walk, you need an introduction to the basic concepts of machine learning prior to focusing on more practical applications. Enter Kaggle’s machine learning tutorial. This seven-lesson course takes about three hours of self-guided learning to complete and will leave you with a solid grounding in machine learning that you can take into more industry-focused courses.

The majority of the seven lessons – barring the first – is split into two parts. First comes a tutorial where you’ll learn about the concepts that the lesson introduces, with the second part being an exercise that tests your new skills. Along the way, you’ll learn the basics of how machine learning models work and why you need them to explore large datasets. Other lessons focus on building and validating a model, with the later lessons introducing more complex algorithms, such as random forests, and giving you a chance to test your skills in competitions.

Though this is a beginner-focused tutorial, you’ll need a solid understanding of Python before making a start. Without experience in this programming language, you’ll feel like you’re truly lost in a random forest before you ever get to learn what that term actually means. On the plus side, the tutorial has an active discussion community (which includes the course instructor Dan Becker) that can help you along and point you in the direction of other courses that supplement this one.

Tutorial 2 – Making Developers Awesome at Machine Learning (Machine Learning Mastery)

This machine learning tutorial is less a structured course and more a series of articles and step-by-step instructional lessons that take you from the foundations of machine learning to more advanced concepts. That method of breaking the course into multiple stages is ideal for students of all experience levels. Complete beginners can start with the “Foundations” level and work their way up while those with more experience can dip into specific subjects that give them trouble or will build on their existing skills.

The course is split into four sections – Foundations, Beginner, Intermediate, and Advanced. At the Foundations level, you’ll learn about the statistical concepts and models that underpin machine learning, giving you a solid basis to move into the Python programming taught in the Beginner section. Once you have a grasp of Python, the Intermediate section teaches you about deep learning and how to code machine learning algorithms. By the time you hit the Advanced stage, you’ll be working on complex subjects like computer vision and natural language processing.

With its less structured nature, this tutorial is great for people who want to dip in and out and those who need to hone in on a specific aspect of machine learning. It’s also a good choice for beginners because it covers practically everything you’ll need to know. Unfortunately, the lack of structure means you don’t get an official certification from the tutorial. Some students may also not like the “hub” nature of the tutorial, as it links you to tons of different web pages that can lead to confusion over time.

Tutorial 3 – Machine Learning Crash Course With TensorFlow APIs (Google)

If you already have a mathematical foundation (as well as some basic understanding of machine learning), Google’s tutorial helps you take your skills to the next level. You’ll need to understand algebra, statistics, and basic trigonometry, in addition to having some understanding of Python, to get started. But assuming you have all of that, this machine learning tutorial exposes you to real-world examples of the technology in action.

It’s a 25-lesson course that contains 30 exercises covering topics like model development and testing, data representation, and building neural networks. According to Google, it takes about 15 hours of self-guided study to complete, though your time may vary depending on how much you already know before you start the course.

The biggest advantage of this tutorial is the name attached to it. Google is a major player in the tech industry and the presence of its name on your CV instantly shows employers that you know your stuff. The course material is also delivered by lecturers who work at or for Google, allowing them to bring their real-world experiences into their lessons. On the downside, the tutorial’s prerequisites make it unsuitable for beginners, though Google does offer more basic courses (both in machine learning and Python) to help you build the required foundation.

Factors to Consider When Choosing a Machine Learning Tutorial

The three options presented above all make a solid case for the best online tutorial for machine learning, though each offers something different based on your current skill level. To make the best choice between the three (and any other tutorials you find) you should consider these factors before committing yourself.

Your Current Skill Level

Diving into neural networks before you even know how machine learning works is like trying to row upstream without a paddle. You’re going to get stuck in rough waters and the end result won’t be what you want it to be. Be honest with yourself about your current skill level to ensure you don’t start a tutorial that’s too difficult (or too simple) for your abilities.

Programming Languages

There’s no getting away from the fact that you’ll need to feel comfortable with programming before taking a machine learning tutorial. Specifically, you’re likely to need some knowledge of Python, though how much depends on the course you take. Other languages can help, at least in the sense of ensuring you’re familiar with programming, but you need to check the language the course uses before starting.

Specific Topics

Though the basic idea of building a machine “brain” is simple enough to understand, the machine learning waters run deep. There are tons of topics and potential specializations you could study, and not all are useful for your intended career path. Check what the course covers and ensure those topics align with what you hope to achieve once you’ve completed the tutorial.

Time Commitment

If a tutorial takes an hour or two to complete, you don’t really need to worry about how you’ll fit it around your other commitments. But if it takes you down a machine learning rabbit hole (i.e., the Machine Learning Mastery Course), you need to get serious with scheduling. Figure out how much time you can commit to your course per week and choose a tutorial that fits around your commitments.

The Cost

On the plus side, many machine learning tutorials are available free of charge. But if you’re looking for more official certification, or you want to take a more formal course, you’ll usually have to pay for the privilege. Weigh up the course’s cost against the benefit you get out of the backend.

Tips for Getting the Most Out of a Machine Learning Tutorial

Anybody can start a machine learning tutorial, but only the truly committed will complete and actually get the most out of the materials. Follow these tips to ensure you’re spending your time wisely on the tutorial you choose:

  • Set clear goals from the outset that define what you want to achieve with the tutorial and where it’s supposed to lead you.
  • Dedicate time to learning every week because regularity is the key to making the information you absorb stick in your mind.
  • Engage with any communities related to your tutorial to learn from your peers and ask questions about the tutorial’s content.
  • Apply what you learn to real-world problems, either via the course itself or by searching for examples of what you’ve learned being put into action.
  • Update your knowledge and skills regularly with further tutorials because what you learn today may be out of date tomorrow.

Find the Best Online Tutorial for Machine Learning for You

There is no single “best” machine learning tutorial on the web because each approaches the subject differently. Some assume you have no knowledge at all and will start with basics before moving you into deeper subjects. Others require you to understand the computing concepts (mathematical and programmatical) that underpin machine learning before you can get started. Understand what the course offers, and what it needs from you, before you get started.

Regardless of your choice, getting started is the most important thing you can do. Once you’ve chosen a tutorial, commit yourself to it fully to take your first step (or potentially a giant leap) into a career that’s only going to grow as machine learning models become more common in business.

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The Value of Hackathons
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Jan 5, 2026 6 min read

Bring talented tech experts together, set them a challenge, and give them a deadline. Then, let them loose and watch the magic happen. That, in a nutshell, is what hackathons are all about. They’re proven to be among the most productive tech events when it comes to solving problems and accelerating innovation.

What Is a Hackathon?

Put simply, a hackathon is a short-term event – often lasting just a couple of days, or sometimes even only a matter of hours – where tech experts come together to solve a specific problem or come up with ideas based on a central theme or topic. As an example, teams might be tasked with discovering a new way to use AI in marketing or to create an app aimed at improving student life.

The term combines the words “hack” and “marathon,” due to how participants (hackers or programmers) are encouraged to work around-the-clock to create a prototype, proof-of-concept, or new solution. It’s similar to how marathon runners are encouraged to keep running, putting their skills and endurance to the test in a race to the finish line.

The Benefits of Hackathons

Hackathons provide value both for the companies that organize them and the people who take part. Companies can use them to quickly discover new ideas or overcome challenges, for example, while participants can enjoy testing their skills, innovating, networking, and working either alone or as part of a larger team.

Benefits for Companies and Sponsors

Many of the world’s biggest brands have come to rely on hackathons as ways to drive innovation and uncover new products, services, and opportunities. Meta, for example, the brand behind Facebook, has organized dozens of hackathons, some of which have led to the development of well-known Facebook features, like the “Like” button. Here’s how hackathons help companies:

  • Accelerate Innovation: In fast-moving fields like technology, companies can’t always afford to spend months or years working on new products or features. They need to be able to solve problems quickly, and hackathons create the necessary conditions to deliver rapid success.
  • Employee Development: Leading companies like Meta have started to use annual hackathons as a way to not only test their workforce’s skills but to give employees opportunities to push themselves and broaden their skill sets.
  • Internal Networking: Hackathons also double up as networking events. They give employees from different teams, departments, or branches the chance to work with and learn from one another. This, in turn, can promote or reinforce team-oriented work cultures.
  • Talent Spotting: Talents sometimes go unnoticed, but hackathons give your workforce’s hidden gems a chance to shine. They’re terrific opportunities to see who your best problem solvers and most creative thinkers at.
  • Improving Reputation: Organizing regular hackathons helps set companies apart from their competitors, demonstrating their commitment to innovation and their willingness to embrace new ideas. If you want your brand to seem more forward-thinking and innovative, embracing hackathons is a great way to go about it.

Benefits for Participants

The hackers, developers, students, engineers, and other people who take part in hackathons arguably enjoy even bigger and better benefits than the businesses behind them. These events are often invaluable when it comes to upskilling, networking, and growing, both personally and professionally. Here are some of the main benefits for participants, explained:

  • Learning and Improvement: Hackathons are golden opportunities for participants to gain knowledge and skills. They essentially force people to work together, sharing ideas, contributing to the collective, and pushing their own boundaries in pursuit of a common goal.
  • Networking: While some hackathons are purely internal, others bring together different teams or groups of people from different schools, businesses, and places around the world. This can be wonderful for forming connections with like-minded individuals.
  • Sense of Pride: Everyone feels a sense of pride after accomplishing a project or achieving a goal, but this often comes at the end of weeks or months of effort. With hackathons, participants can enjoy that same satisfying feeling after just a few hours or a couple of days of hard work.
  • Testing Oneself: A hackathon is an amazing chance to put one’s skills to the test and see what one is truly capable of when given a set goal to aim for and a deadline to meet. Many participants are surprised to see how well they respond to these conditions.
  • Boosting Skills: Hackathons provide the necessary conditions to hone and improve a range of core soft skills, such as teamwork, communication, problem-solving, organization, and punctuality. By the end, participants often emerge with more confidence in their abilities.

Hackathons at OPIT

The Open Institute of Technology (OPIT) understands the unique value of hackathons and has played its part in sponsoring these kinds of events in the past. OPIT was one of the sponsors behind ESCPHackathon 6, for example, which involved 120 students given AI-related tasks, with mentorship and guidance from senior professionals and developers from established brands along the way.

Marco Fediuc, one of the participants, summed up the mood in his comments:

“The hackathon was a truly rewarding experience. I had the pleasure of meeting OPIT classmates and staff and getting to know them better, the chance to collaborate with brilliant minds, and the opportunity to take part in an exciting and fun event.

“Participating turned out to be very useful because I had the chance to work in a fast-paced, competitive environment, and it taught me what it means to stay calm and perform under pressure… To prospective Computer Science students, should a similar opportunity arise, I can clearly say: Don’t underestimate yourselves!”

The new year will also see the arrival of OPIT Hackathon 2026, giving more students the chance to test their skills, broaden their networks, and enjoy the one-of-a-kind experiences that these events never fail to deliver. This event is scheduled to be held February 13-15, 2026, and is open to all OPIT Bachelor’s and Master’s students, along with recent graduates. Interested parties have until February 1 to register.

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OPIT’s First Career Fair
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Jan 5, 2026 6 min read

The Open Institute of Technology (OPIT) recently held its first-ever career fair to showcase its wide array of career education options and services. Representatives from numerous high-profile international companies were in attendance, and students enjoyed unprecedented opportunities to connect with business leaders, expand their professional networks, and pave the way for success in their future careers.

Here’s a look back at the event and how it ties into OPIT’s diverse scope of career services.

Introducing OPIT

For those who aren’t yet familiar, OPIT is an EU-accredited Higher Education Institution, offering online degrees in technological fields such as computer science, data science, artificial intelligence, cybersecurity, and digital business. Aimed at making high-level tech education accessible to all, OPIT has assembled a stellar team of tutors and experts to train the tech leaders of tomorrow.

The First OPIT Career Fair

OPIT’s first career fair was held on November 19 and 20. And as with OPIT’s lectures, it was an exclusively online event, which ensured that every attendee had equal access to key lectures and information. Interested potential students from all over the world were able to enjoy the same great experience, demonstrating a core principle that OPIT has championed from the very start – the principles of accessibility and the power of virtual learning.

More than a dozen leading international companies took part in the event, with the full guest list including representatives from:

  • Deloitte
  • Dylog Hitech
  • EDIST Engineering Srl
  • Tinexta Cyber
  • Datapizza
  • RWS Group
  • WE GRELE FRANCE
  • Avatar Investments
  • Planet Farms
  • Coolshop
  • Hoist Finance Italia
  • Gruppo Buffetti S.p.A
  • Nesperia Group
  • Fusion AI Labs
  • Intesi Group
  • Reply
  • Mindsight Ventures

This was a fascinating mix of established enterprises and emerging players. Deloitte, for example, is one of the largest professional services networks in the world in terms of both revenue and number of employees. Mindsight Ventures, meanwhile, is a newer but rapidly emerging name in the fields of AI and business intelligence.

The Response

The first OPIT career fair was a success, with many students in attendance expressing their joy at being able to connect with such a strong lineup of prospective employers.

OPIT Founder and Director Riccardo Ocleppo had this to say:

“I often say internally that our connection with companies – through masterclasses, thesis and capstone projects, and career opportunities – is the ‘cherry on the cake’ of the OPIT experience!

“It’s also a core part of our mission: making higher education more practical, more connected, and more aligned with what happens in the real world.

“Our first Career Fair says a lot about our commitment to building an end-to-end learning and professional growth experience for our community of students.

“Thank you to the Student and Career Services team, and to Stefania Tabi for making this possible.”

Representatives from some of the companies that attended also shared positive impressions of the event. A representative from Nesperia Group, for example, said:

“Nesperia Group would like to thank OPIT for the warm welcome we received during the OPIT Career Day. We were pleased to be part of the event because we met many talented young professionals. Their curiosity and their professional attitude really impressed us, and it’s clear that OPIT is doing an excellent job supporting their growth. We really believe that events like these are important because they can create a strong connection between companies and future professionals.”

The Future

Given the enormous success of the first OPIT career fair, it’s highly likely that students will be able to enjoy more events like this in the years to come. OPIT is clearly committed to making the most of its strong business connections and remarkable network to provide opportunities for growth, development, and employment, bringing students and businesses together.

Future events will continue to allow students to connect with some of the biggest businesses in the world, along with emerging names in the most exciting and innovative tech fields. This should allow OPIT graduates to enter the working world with strong networks and firm connections already established. That, in turn, should make it easier for them to access and enjoy a wealth of beneficial professional opportunities.

Given that OPIT also has partnerships in place with numerous other leading organizations, like Hype, AWS, and Accenture, the number and variety of the companies potentially making appearances at career fairs in the future should no doubt increase dramatically.

Other Career Services at OPIT

The career fair is just one of many ways in which OPIT leverages its company connections and offers professional opportunities and career support to its students. Other key career services include:

  • Career Coaching: Students are able to schedule one-on-one sessions with their own mentors and career advisors. They can receive feedback on their resumes, practice and improve their interview skills, or work on clear action plans that align with their exact professional goals.
  • Resource Hub: The OPIT Resource Hub is jam-packed with helpful guides and other resources to help students plan out and take smart steps in their professional endeavors. With detailed insights and practical tips, it can help tech graduates get off to the best possible start.
  • Career Events: The career fair is only one of several planned career-related events organized by OPIT. Other events are planned to give students the chance to learn from and engage with industry experts and leading tech firms, with workshops, career skills days, and more.
  • Internships: OPIT continues to support students after graduation, offering internship opportunities with leading tech firms around the world. These internships are invaluable for gaining experience and forging connections, setting graduates up for future success.
  • Peer Mentoring: OPIT also offers a peer mentoring program in which existing students can team up with OPIT alumni to enjoy the benefits of their experience and unique insights.

These services – combined with the recent career day – clearly demonstrate OPIT’s commitment to not merely educating the tech leaders of the future, but also to supporting their personal and professional development beyond the field of education, making it easier for them to enter the working world with strong connections and unrivaled opportunities.

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