Data permeates almost every aspect of our lives. Trying to make sense of it all is a Herculean endeavor that would take humans years (if not centuries). But fear not; it’s machine learning to the rescue.

Machine learning algorithms can comb through data in a matter of days or even hours, uncovering valuable insights. Many industries have already experienced numerous benefits of these algorithms, yet the field promises to get even bigger and better.

However, we shouldn’t discard humans just yet. They still play an essential role in this process.

Machine learning algorithms couldn’t parse and interpret data correctly without human guidance. As the machine learning field grows, so will the need for skilled data scientists.

One way to acquire the skills necessary to participate in this game-changing field is by taking a machine learning course. When chosen wisely, this course will provide you with crucial theory and invaluable practice to enter the field with a bang or take your knowledge to the next level.

To ensure you choose the best machine learning course, we’ve compiled a list of our top five online picks.

Factors to Consider When Choosing a Machine Learning Course

Just like data, there are tons of courses online. Taking all of them would not be humanly possible. And frankly, not all of these courses would be worth your time. Remember these factors when browsing online learning platforms, and you’ll pick the best machine learning course each time.

Course Content and Curriculum

Shakespeare once said, “Expectation is the root of all heartache.” Believe it or not, this quote will benefit you immensely when choosing an online machine learning course.

Just because a course is named Machine Learning, it doesn’t mean it will be helpful to you. The only way to ensure the course is worth taking is to check its curriculum. Provided the description isn’t misleading, you’ll immediately know whether the course suits your educational and professional needs.

Instructor’s Expertise and Experience

Who teaches the course is as important as what is taught (if not more). Otherwise, you could just pick up a book on machine learning with the same content and try to make sense of it.

So, when a machine learning course piques your interest, check out the instructor.

Are they considered an authority in machine learning? Are they industry veterans?

A quick Google search will tell you all you need to know.

Course Duration and Flexibility

“Can I fully commit to this course?” That is the question to ask yourself before starting a machine learning course.

One look at the course’s description will tell you whether it takes an hour or months to complete. Also, you’ll immediately know if it is self-paced or fixed-timeline.

Hands-On Projects and Real-World Applications

No one can deny the value of theoretical knowledge in a machine learning course. There’s no moving on without understanding machine learning algorithms and underlying principles.

But how will you learn to use those theoretical concepts in practice? That’s right, through hands-on projects and case studies.

Ideally, your chosen course will strike the perfect balance between the two.

Course Reviews and Ratings

Sure, it’s easy to manipulate reviews and ratings. But it’s even easier to spot the fake ones. So, give the rating page a quick read-through, and you should be able to tell if the course is any good.

Certification and Accreditation

Certified and accredited courses are a must for those serious about a career in machine learning. Of course, these courses are rarely free. But if they help you land your dream job, the investment will be well worth it.

Top Picks for the Best Machine Learning Courses

We’ve also considered the above-mentioned factors when choosing our top picks for online machine learning courses. Without further ado, check out the best ones to help you learn or improve machine learning skills.

Supervised Machine Learning: Regression and Classification

This course has a lot of things going for it. It was one of the courses that popularized the entire concept of massive open online courses. And it is taught by none other than Andrew Ng, a pioneer and a visionary leader in machine learning and artificial intelligence (AI). In other words, this course is the gold standard by which every machine learning course is evaluated.

Here are all the important details at a glance:

  • The course is beginner-friendly and features flexible deadlines.
  • It lasts 11 weeks, each covering different machine learning techniques and models (six hours per week).
  • It covers the fundamentals of machine learning and teaches you how to apply them.
  • The skills you will gain include regularization to avoid overfitting, gradient descent, supervised learning, and linear regression.
  • You’ll earn a certificate after completing the course.

The only thing to note about the certificate is that you must sign up for a Coursera membership ($39/€36 a month) to receive it. Otherwise, you can audit the course for free. To apply, you only need to create a Coursera account and press the “Enroll” button.

Machine Learning With Python

Another fan-favorite on Coursera, this machine learning course uses Python (SciPy and scikit-learn libraries). It’s offered by IBM, a company at the forefront of machine learning and AI research.

Here’s what you need to know about this course:

  • The course is beginner-friendly but requires a great deal of calculus knowledge.
  • It’s divided into four weeks, each dedicated to one broad machine learning task (regression, clustering, classification, and their implementation).
  • By the end of the course, you’ll learn the theoretical fundamentals and numerous real-world applications of machine learning.
  • The emphasis is placed on hands-on learning.
  • A certificate is available, provided you apply for a Coursera membership ($39/€36 a month).

A Coursera account is all you need to apply for this course. You can start with a 7-day free trial. You’ll have to pay $39 (approximately €36) a month to continue learning.

Machine Learning Crash Course

Google’s Machine Learning Crash Course is ideal for those who want a fast-paced approach to learning machine learning. This intensive course uses TensorFlow, Google’s popular open-source machine learning framework.

Check out these facts to determine whether this is the best machine learning course for you:

  • You can take this course as a beginner if you read some additional resources before starting.
  • The course consists of 25 lessons that you can complete in 15 hours.
  • Google researchers present the lessons.
  • It perfectly combines theoretical video lectures (machine learning concepts and engineering), real-world case studies, and hands-on exercises.
  • No certificate is issued upon completion.

Enrolling in this course is pretty straightforward – just click the “Start Crash Course” button. The course is free of charge.

Machine Learning A-Z: Hands-On Python & R in Data Science

As its name implies, this Udemy course is pretty comprehensive. Two data scientists teach it, primarily focusing on practical experiences (learning to create machine learning algorithms). If you feel like you’re missing hands-on experience in machine learning, this is the course for you.

Before applying, consider the following information:

  • The course can be beginner-friendly, provided you have solid mathematics knowledge.
  • It consists of video lessons and practical exercises (around 40 hours total).
  • The introductory portion focuses on regression, classification, and clustering models.
  • You’ll receive a certificate of completion.

To gain lifetime access to this course, you’ll need to pay $89.99 (a little over €83). Applying for it is a matter of creating an Udemy account and purchasing the course.

Machine Learning Specialization

This advanced course is the course you want to take when mastering your knowledge of machine learning. Or perhaps we should say courses since this specialization consists of six separate courses. The program was created by Andrew Ng, who also serves as an instructor (one of four total).

Here’s a quick overview of the course’s key features:

  • The course isn’t beginner-friendly; it’s intermediate level and requires previous experience.
  • At a pace of three hours per week, it takes approximately seven months to complete.
  • The course focuses on numerous practical skills, including Python programming, linear regression, and decision trees.
  • Each course includes a hands-on project.
  • You’re awarded a shareable certificate upon completion of each course in the specialization.

To begin this challenging yet rewarding journey, create a Coursera account and enroll in the specialization. Then, you can choose the first course—the entire specialization costs around $350 (close to €324).

Additional Resources for Learning Machine Learning

The more you immerse yourself in machine learning, the faster you advance. So, besides attending a machine learning course, consider exploring additional learning resources, such as:

  • Books and e-books. Books on machine learning provide in-depth explanations of the topic. So, if you feel that a course’s content is insufficient, this is the path for you. Check out “Introduction to Statistical Learning” (theory-focused) and “Hands-On Machine Learning With Scikit-Learn and TensorFlow.
  • Online tutorials and blogs. Due to the complexity of the field, only a few bloggers post consistently on the topic. Still, blogs like Christopher Olah and Machine Learning Mastery are updated relatively frequently and contain plenty of fascinating information.
  • Podcasts and YouTube channels. Keep up with the latest news in machine learning with podcasts like “This Week in Machine Learning and AI.” YouTube channels like Stanford Online also offer a treasure trove of valuable information on the topic.
  • Networking and community involvement. You can learn much about machine learning by sharing insights and ideas with like-minded individuals. Connect with the machine learning community through courses or conferences (AI & Big Data Expo World Series, MLconf).

Master Machine Learning to Transform Your Future

An online machine learning course allows you to learn directly from the best of the best, whether individuals like Andrew Ng or prominent organizations like Google and IBM. Once you start this exciting journey, you probably won’t want to stop. And considering all the career prospects machine learning can bring, why would you?

If you see a future in computer science, consider pursuing a degree from the Open Institute of Technology. Besides machine learning, you’ll acquire all the necessary skills to succeed in this ever-evolving and lucrative field.

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New OPIT Degrees launching (soon)!
Riccardo Ocleppo
Riccardo Ocleppo
Nov 29, 2023 2 min read


Soon, we will be launching four new Degrees for AY24-25 at OPIT – Open Institute of Technology
I want to offer a behind-the-scenes look at the Product Definition process that has shaped these upcoming programs.

🚀 Phase 1: Discovery (Late May – End of July)

Our journey began with intensive brainstorming sessions with OPIT’s Academic Board (Francesco Profumo, Lorenzo Livi, Alexiei Dingli, Andrea Pescino, Rosario Maccarrone) . We also conducted 50+ interviews with tech and digital entrepreneurs (both from startups and established firms), academics and students. Finally, we deep-dived into the “Future of Jobs 2023” report by the World Economic Forum and other valuable research.

🔍 Phase 2: Selection – Crafting Our Roadmap (July – August)

Our focus? Introducing new degrees addressing critical workforce shortages and upskilling/reskilling needs for the next 5-10 years, promising significant societal impact and a broad market reach.
Our decision? To channel our energies on full BScs and MScs, and steer away from shorter courses or corporate-focused offerings. This aligns perfectly with our core mission.

💡 Focus Areas Unveiled!

We’re thrilled to concentrate on pivotal fields like:

  • Cybersecurity
  • Advanced AI
  • Digital Business
  • Metaverse & Gaming
  • Cloud Computing (less “glamorous”, but market demand is undeniable).

🎓 Phase 3: Definition – Shaping the Degrees (August – November)

With an expert in each of the above fields, and with the strong collaboration of our Academic Director, Prof. Lorenzo Livi , we embarked on a rigorous “drill-down process”. Our goal? To meld modern theoretical knowledge with cutting-edge competencies and skills. This phase included interviewing over 60+ top academics, industry professionals, and students and get valuable, program-specific, insights from our Marketing department.

🌟 Phase 4: Accreditation and Launch – The Final Stretch

We’re currently in the accreditation process, gearing up for the launch. The focus is now shifting towards marketing, working closely with Greta Maiocchi and her Marketing and Admissions team. Together, we’re translating our new academic offering into a compelling value proposition for the market.

Stay tuned for more updates!

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Five Reasons to Study Online at OPIT
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Nov 29, 2023 9 min read

Far from being a temporary educational measure that came into its own during the pandemic, online education is providing students from all over the world with new ways to learn. That’s proven by statistics from Oxford Learning College, which point out that over 100 million students are now enrolled in some form of online course.

The demand for these types of courses clearly exists.

In fact, the same organization indicates that educational facilities that introduce online learning see a 42% increase in income – on average – suggesting that the demand is there.

Enter the Open Institute of Technology (OPIT).

Delivering three online courses – a Bachelor’s degree in computer science and two Master’s degrees – with more to come, OPIT is positioning itself as a leader in the online education space. But why is that? After all, many institutions are making the jump to e-learning, so what separates OPIT from the pack?

Here, you’ll discover the answers as you delve into the five reasons why you should trust OPIT for your online education.

Reason 1 – A Practical Approach

OPIT focuses on computer science education – a field in which theory often dominates the educational landscape. The organization’s Rector, Professor Francesco Profumo, makes this clear in a press release from June 2023. He points to a misalignment between what educators are teaching computer science students and what the labor market actually needs from those students as a key problem.

“The starting point is the awareness of the misalignment,” he says when talking about how OPIT structures its online courses. “That so-called mismatch is generated by too much theory and too little practical approach.” In other words, students in many classes spend far too much time learning the “hows” and “whys” behind computerized systems without actually getting their hands dirty with real work that gives them practical experience in using those systems.

OPIT takes a different approach.

It has developed a didactic approach that focuses far more on the practical element than other courses. That approach is delivered through a combination of classroom sessions – such as live lessons and masterclasses – and practical work offered through quizzes and exercises that mimic real-world situations.

An OPIT student doesn’t simply learn how computers work. They put their skills into practice through direct programming and application, equipping them with skills that are extremely attractive to major employers in the tech field and beyond.

Reason 2 – Flexibility Combined With Support

Flexibility in how you study is one of the main benefits of any online course.

You control when you learn and how you do it, creating an environment that’s beneficial to your education rather than being forced into a classroom setting with which you may not feel comfortable. This is hardly new ground. Any online educational platform can claim that it offers “flexibility” simply because it provides courses via the web.

Where OPIT differs is that it combines that flexibility with unparalleled support bolstered by the experiences of teachers employed from all over the world. The founder and director of OPIT, Riccardo Ocleppo, sheds more light on this difference in approach when he says, “We believe that education, even if it takes place physically at a distance, must guarantee closeness on all other aspects.” That closeness starts with the support offered to students throughout their entire study period.

Tutors are accessible to students at all times. Plus, every participant benefits from weekly professor interactions, ensuring they aren’t left feeling stuck on an educational “island” and have to rely solely on themselves for their education. OPIT further counters the potential isolation that comes with online learning with a Student Support team to guide students through any difficulties they may have with their courses.

In this focus on support, OPIT showcases one of its main differences from other online platforms.

You don’t simply receive course material before being told to “get on with it.” You have the flexibility to learn at your own pace while also having a support structure that serves as a foundation for that learning.

Reason 3 – OPIT Can Adapt to Change Quickly

The field of computer science is constantly evolving.

In the 2020s alone, we’ve seen the rise of generative AI – spurred on by the explosive success of services like ChatGPT – and how those new technologies have changed the way that people use computers.

Riccardo Ocleppo has seen the impact that these constant evolutions have had on students. Before founding OPIT, he was an entrepreneur who received first-hand experience of the fact that many traditional educational institutions struggle to adapt to change.

“Traditional educational institutions are very slow to adapt to this wave of new technologies and trends within the educational sector,” he says. He points to computer science as a particular issue, highlighting the example of a board in Italy of which he is a member. That board – packed with some of the country’s most prestigious tech universities – spent three years eventually deciding to add just two modules on new and emerging technologies to their study programs.

That left Ocleppo feeling frustrated.

When he founded OPIT, he did so intending to make it an adaptable institution in which courses were informed by what the industry needs. Every member of its faculty is not only a superb teacher but also somebody with experience working in industry. Speaking of industry, OPIT collaborates with major companies in the tech field to ensure its courses deliver the skills that those organizations expect from new candidates.

This confronts frustration on both sides. For companies, an OPIT graduate is one for which they don’t need to bridge a “skill gap” between what they’ve learned and what the company needs. For you, as a student, it means that you’re developing skills that make you a more desirable prospect once you have your degree.

Reason 4 – OPIT Delivers Tier One Education

Despite their popularity, online courses can still carry a stigma of not being “legitimate” in the face of more traditional degrees. Ocleppo is acutely aware of this fact, which is why he’s quick to point out that OPIT always aims to deliver a Tier One education in the computer science field.

“That means putting together the best professors who create superb learning material, all brought together with a teaching methodology that leverages the advancements made in online teaching,” he says.

OPIT’s degrees are all accredited by the European Union to support this approach, ensuring they carry as much weight as any other European degree. It’s accredited by both the European Qualification Framework (EQF) and the Malta Qualification Framework (MQF), with all of its courses having full legal value throughout Europe.

It’s also here where we see OPIT’s approach to practicality come into play via its course structuring.

Take its Bachelor’s degree in computer science as an example.

Yes, that course starts with a focus on theoretical and foundational knowledge. Building a computer and understanding how the device processes instructions is vital information from a programming perspective. But once those foundations are in place, OPIT delivers on its promises of covering the most current topics in the field.

Machine learning, cloud computing, data science, artificial intelligence, and cybersecurity – all valuable to employers – are taught at the undergraduate level. Students benefit from a broader approach to computer science than most institutions are capable of, rather than bogging them down in theory that serves little practical purpose.

Reason 5 – The Learning Experience

Let’s wrap up by honing in on what it’s actually like for students to learn with OPIT.

After all, as Ocleppo points out, one of the main challenges with online education is that students rarely have defined checkpoints to follow. They can start feeling lost in the process, confronted with a metaphorical ocean of information they need to learn, all in service of one big exam at the end.

Alternatively, some students may feel the temptation to not work through the materials thoroughly, focusing instead on passing a final exam. The result is that those students may pass, but they do so without a full grasp of what they’ve learned – a nightmare for employers who already have skill gaps to handle.

OPIT confronts both challenges by focusing on a continuous learning methodology. Assessments – primarily practical – take place throughout the course, serving as much-needed checkpoints for evaluating progress. When combined with the previously mentioned support that OPIT offers, this approach has led to courses that are created from scratch in service of the student’s actual needs.

Choose OPIT for Your Computer Science Education

At OPIT, the focus lies as much on helping students to achieve their dream careers as it does on teaching them. All courses are built collaboratively. With a dedicated faculty combined with major industry players, such as Google and Microsoft, it delivers materials that bridge the skill gap seen in the computer science field today.

There’s also more to come.

Beyond the three degrees OPIT offers, the institution plans to add more. Game development, data science, and cloud computing, to name a few, will receive dedicated degrees in the coming months, accentuating OPIT’s dedication to adapting to the continuous evolution of the computer science industry. Discover OPIT today – your journey into computing starts with the best online education institution available.

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