The Open Institute of Technology (OPIT) is a unique institution through and through. From an unparalleled support team that guides you every step of the way to state-of-the-art virtual resources, OPIT redefines online learning. This institution also proves that online education can be as enriching as its traditional counterpart. Better yet, it can outperform it in numerous aspects.

This fact alone begs the question – how did it all begin?

To answer this question, we’ll go straight to the source – the founder of OPIT, Riccardo Ocleppo.

In this article, Riccardo will walk us through his journey of envisioning (and building) OPIT and transforming online education in the process.

The Pre-OPIT Years: Where It All Began

To understand how Riccardo came up with the idea for OPIT, we must travel back to the year 2006. That’s when Riccardo graduated from Politecnico di Torino with a bachelor’s in electronics engineering.

This institution is arguably the most prestigious in Italy (and one of the most reputable in Europe). So, it shouldn’t be surprising that Riccardo chose to continue his education here, pursuing a master’s degree.

He completed the master’s program in 2008 and did so with honors.

Yet, Riccardo couldn’t shake the impression that it was all in vain. In his words, “When I left the university, I had the impression that I could do very little, and I knew very little that could help me in my professional endeavors.”

But Riccardo decided not to sit idly by.

He saw it this way – it might be too late for him, as he was done with his studies. But it’s certainly not too late for future students who deserve a better education. That’s why, only two years later, in 2010, he founded Docsity.

Docsity is an online social learning network with over 20 million registered students. Thanks to this network, over 250 universities worldwide received help in improving their study programs (and finding students).

Docsity also gave Riccardo a chance to fully immerse himself into the education sector for over a decade, finding new ways to reform it from within.

OPIT’s Inception: From Vision to Reality

With the knowledge (and the resources) from Docsity, Riccardo started working on a platform designed to provide the kind of education he wished he had received. The platform in question was, of course, the Open Institute of Technology.

The primary goal of OPIT was to bridge the gap between “what students expect, what companies need, and what higher-level institutions actually deliver in terms of training and education.”

From Riccardo’s experience, this gap was pretty huge. Remember that even with a bachelor’s and a master’s degree in electronics engineering, he felt he had little to offer to companies.

This perceived shortcoming primarily comes from the fact he received a lot of theory at the university but very little practice. And that’s not to mention how outdated the curriculum was, as well as laser-focused on electronics engineering. In other words, bid farewell to “competencies on the most recent technologies and project management methodologies.”

This perspective made him determined to create a holistic educational solution. Or, as Riccardo puts it, “When designing OPIT’s degree programs to address the skills in high demand today, we chose to start from scratch to go beyond the limits of traditional higher education.”

At OPIT, you’ll receive valuable knowledge beyond theory. Essentially, OPIT equips you with everything you need to enter the job market, ready to excel in your field from day one (or day zero, as Riccardo calls it!).

Tailored for Triumph: OPIT’s Unique Programs

Designing any online curriculum is no easy task. However, the computer science field comes with its unique set of challenges. Why?

This field is constantly evolving. That’s what makes it difficult for most traditional higher education institutions to keep up. As Riccardo puts it, “[These institutions] are very slow to adapt to this wave of new technologies and new trends within the educational sector.” Of course, thanks to Docsity, Riccardo speaks from extensive experience, as he’s seen “multiple times how difficult it is to help these institutions update their study curriculum.”

Companies have it no easier.

Riccardo says, “A company needs one to two years to make people that should be trained on today’s technologies and on today’s skills effectively enter the job market and be productive when they enter these companies.”

Again, Riccardo speaks from personal experience. As a founder of a tech company (and a manager in others), he was tasked with creating and managing big tech teams on several occasions. However, despite interviewing hundreds of candidates, he couldn’t find those trained in today’s technologies, not those from 20 years ago.

With this in mind, he designed OPIT’s curriculum to effectively “train the next generation of leaders and managers in the field of computer science.” Many people helped him in this endeavor, chief among them Professor Francesco Profumo, current head of institution at OPIT and former Minister of Education in Italy.

This unique approach makes OPIT’s programs different in terms of how they’ve been conceived and how they’ll be delivered.

Take the Bachelor of Science (BSc) in Modern Computer Science program as an example.

Riccardo says that to be a great programmer, “you cannot just dive into programming itself.” First, you must understand how a computer is built and how its various units operate and communicate. This way, you’ll have no issues debugging a code in the future since you’ll understand the underlying mechanisms.

These underlying systems and foundational skills are precisely what is taught during the first term of the modern computer science program. Afterward, you’ll move toward the latest advancements in computer science, including machine learning, artificial intelligence, data science, cybersecurity, and cloud computing. This way, you’ll have quite a broad perspective on computer science, rarely seen in other educational programs, online or offline.

It also means you won’t have to specialize in a particular field, as you’re forced to do with many other programs. In Riccardo’s opinion, the master’s degree is where you should begin your specialization journey.

OPIT offers as many as four master’s degree programs, but Riccardo focuses on Applied Data Science & AI this time.

In Riccardo’s words, “The whole purpose of this [program] is actually to train people that do not want to pursue a super technical career but actually want to pursue a career at the intersection between the tech and the management of a company.” In other words, individuals who complete this program will acquire all the necessary tech skills. However, they’ll also be able to ensure the tech team is “correctly understood by the management of the company,” thanks to the managerial skills earned during the program.

Of course, this program also covers all the essential theoretical knowledge, from Python to machine learning. But it also has a solid applicative angle, teaching students how to use the most valuable tools available in today’s market. Simply put, you’re training “for what you’ll be doing when you enter your next job.”

 

Breaking the Mold: What Sets OPIT Apart

The unique curriculum isn’t the only thing that sets OPIT apart from other higher education institutions in the same field. Here’s what Riccardo singles out as OPIT’s most appealing characteristics.

Continuous Assessment

Learning at your own pace can be a double-edged sword. On the one hand, you have all the flexibility and freedom to organize your studies (and life). On the other, you might start procrastinating without a traditional daily commitment of in-classroom learning.

OPIT ensures this unfortunate scenario never happens by doing away with one big final exam you must cram for. Instead, you’ll be continuously assessed throughout the program, allowing you a much better approach to learning and a deeper understanding of the subject matter.

As Riccardo puts it, OPIT will give you “multiple checkpoints,” preventing you from getting “lost” throughout the learning process.

New Learning Resources

According to Riccardo, most of today’s available resources were created for the “oldest wave of education.” That’s why he (and his team) created all OPIT resources and learning materials from scratch, giving you a fresh perspective on the tech world. These resources also come in the form of engaging videos, which are short enough to keep you fully focused yet detailed enough to provide a deep understanding of the topic.

World-Class Professors

Let’s not sugarcoat it – modern resources mean nothing if the professors teaching them still stick to old-school principles and approaches. Luckily, this isn’t the case with OPIT’s faculty.

Every member of this faculty has been carefully selected based on their academic expertise, business experience, and global perspective. These professors aim to “help you learn in a more engaging and interesting way,” as Riccardo puts it.

He also adds that OPIT’s faculty breaks away from the common saying in academics, “Those who can’t do, teach.” In his words, “We didn’t want to have people that can teach because they cannot do,” so that’s the standard he prioritized when bringing people on board.

Future-Proof Your Career

Now that you know the fascinating tale of OPIT’s conception, all that’s left to do is to get in touch with our team of experts and take the first step in future-proofing your career. As you’ve already seen, OPIT will take care of most of the subsequent steps. All you need is a desire to learn and an interest in developing new skills, and success is imminent.

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Agenda Digitale: The Five Pillars of the Cloud According to NIST – A Compass for Businesses and Public Administrations
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Jun 26, 2025 7 min read

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By Lokesh Vij, Professor of Cloud Computing Infrastructure, Cloud Development, Cloud Computing Automation and Ops and Cloud Data Stacks at OPIT – Open Institute of Technology

NIST identifies five key characteristics of cloud computing: on-demand self-service, network access, resource pooling, elasticity, and metered service. These pillars explain the success of the global cloud market of 912 billion in 2025

In less than twenty years, the cloud has gone from a curiosity to an indispensable infrastructure. According to Precedence Research, the global market will reach 912 billion dollars in 2025 and will exceed 5.1 trillion in 2034. In Europe, the expected spending for 2025 will be almost 202 billion dollars. At the base of this success are five characteristics, identified by the NIST (National Institute of Standards and Technology): on-demand self-service, network access, shared resource pool, elasticity and measured service.

Understanding them means understanding why the cloud is the engine of digital transformation.

On-demand self-service: instant provisioning

The journey through the five pillars starts with the ability to put IT in the hands of users.

Without instant provisioning, the other benefits of the cloud remain potential. Users can turn resources on and off with a click or via API, without tickets or waiting. Provisioning a VM, database, or Kubernetes cluster takes seconds, not weeks, reducing time to market and encouraging continuous experimentation. A DevOps team that releases microservices multiple times a day or a fintech that tests dozens of credit-scoring models in parallel benefit from this immediacy. In OPIT labs, students create complete Kubernetes environments in two minutes, run load tests, and tear them down as soon as they’re done, paying only for the actual minutes.

Similarly, a biomedical research group can temporarily allocate hundreds of GPUs to train a deep-learning model and release them immediately afterwards, without tying up capital in hardware that will age rapidly. This flexibility allows the user to adapt resources to their needs in real time. There are no hard and fast constraints: you can activate a single machine and deactivate it when it is no longer needed, or start dozens of extra instances for a limited time and then release them. You only pay for what you actually use, without waste.

Wide network access: applications that follow the user everywhere

Once access to resources is made instantaneous, it is necessary to ensure that these resources are accessible from any location and device, maintaining a uniform user experience. The cloud lives on the network and guarantees ubiquity and independence from the device.

A web app based on HTTP/S can be used from a laptop, tablet or smartphone, without the user knowing where the containers are running. Geographic transparency allows for multi-channel strategies: you start a purchase on your phone and complete it on your desktop without interruptions. For the PA, this means providing digital identities everywhere, for the private sector, offering 24/7 customer service.

Broad access moves security from the physical perimeter to the digital identity and introduces zero-trust architecture, where every request is authenticated and authorized regardless of the user’s location.

All you need is a network connection to use the resources: from the office, from home or on the move, from computers and mobile devices. Access is independent of the platform used and occurs via standard web protocols and interfaces, ensuring interoperability.

Shared Resource Pools: The Economy of Scale of Multi-Tenancy

Ubiquitous access would be prohibitive without a sustainable economic model. This is where infrastructure sharing comes in.

The cloud provider’s infrastructure aggregates and shares computational resources among multiple users according to a multi-tenant model. The economies of scale of hyperscale data centers reduce costs and emissions, putting cutting-edge technologies within the reach of startups and SMBs.

Pooling centralizes patching, security, and capacity planning, freeing IT teams from repetitive tasks and reducing the company’s carbon footprint. Providers reinvest energy savings in next-generation hardware and immersion cooling research programs, amplifying the collective benefit.

Rapid Elasticity: Scaling at the Speed ​​of Business

Sharing resources is only effective if their allocation follows business demand in real time. With elasticity, the infrastructure expands or reduces resources in minutes following the load. The system behaves like a rubber band: if more power or more instances are needed to deal with a traffic spike, it automatically scales in real time; when demand drops, the additional resources are deactivated just as quickly.

This flexibility seems to offer unlimited resources. In practice, a company no longer has to buy excess servers to cover peaks in demand (which would remain unused during periods of low activity), but can obtain additional capacity from the cloud only when needed. The economic advantage is considerable: large initial investments are avoided and only the capacity actually used during peak periods is paid for.

In the OPIT cloud automation lab, students simulate a streaming platform that creates new Kubernetes pods as viewers increase and deletes them when the audience drops: a concrete example of balancing user experience and cost control. The effect is twofold: the user does not suffer slowdowns and the company avoids tying up capital in underutilized servers.

Metered Service: Transparency and Cost Governance

The dynamic scale generated by elasticity requires precise visibility into consumption and expenses : without measurement there is no governance. Metering makes every second of CPU, every gigabyte and every API call visible. Every consumption parameter is tracked and made available in transparent reports.

This data enables pay-per-use pricing , i.e. charges proportional to actual usage. For the customer, this translates into variable costs: you only pay for the resources actually consumed. Transparency helps you plan your budget: thanks to real-time data, it is easier to optimize expenses, for example by turning off unused resources. This eliminates unnecessary fixed costs, encouraging efficient use of resources.

The systemic value of the five pillars

When the five pillars work together, the effect is multiplier . Self-service and elasticity enable rapid response to workload changes, increasing or decreasing resources in real time, and fuel continuous experimentation; ubiquitous access and pooling provide global scalability; measurement ensures economic and environmental sustainability.

It is no surprise that the Italian market will grow from $12.4 billion in 2025 to $31.7 billion in 2030 with a CAGR of 20.6%. Manufacturers and retailers are migrating mission-critical loads to cloud-native platforms , gaining real-time data insights and reducing time to value .

From the laboratory to the business strategy

From theory to practice: the NIST pillars become a compass for the digital transformation of companies and Public Administration. In the classroom, we start with concrete exercises – such as the stress test of a video platform – to demonstrate the real impact of the five pillars on performance, costs and environmental KPIs.

The same approach can guide CIOs and innovators: if processes, governance and culture embody self-service, ubiquity, pooling, elasticity and measurement, the organization is ready to capture the full value of the cloud. Otherwise, it is necessary to recalibrate the strategy by investing in training, pilot projects and partnerships with providers. The NIST pillars thus confirm themselves not only as a classification model, but as the toolbox with which to build data-driven and sustainable enterprises.

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ChatGPT Action Figures & Responsible Artificial Intelligence
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Jun 23, 2025 6 min read

You’ve probably seen two of the most recent popular social media trends. The first is creating and posting your personalized action figure version of yourself, complete with personalized accessories, from a yoga mat to your favorite musical instrument. There is also the Studio Ghibli trend, which creates an image of you in the style of a character from one of the animation studio’s popular films.

Both of these are possible thanks to OpenAI’s GPT-4o-powered image generator. But what are you risking when you upload a picture to generate this kind of content? More than you might imagine, according to Tom Vazdar, chair of cybersecurity at the Open Institute of Technology (OPIT), in a recent interview with Wired. Let’s take a closer look at the risks and how this issue ties into the issue of responsible artificial intelligence.

Uploading Your Image

To get a personalized image of yourself back from ChatGPT, you need to upload an actual photo, or potentially multiple images, and tell ChatGPT what you want. But in addition to using your image to generate content for you, OpenAI could also be using your willingly submitted image to help train its AI model. Vazdar, who is also CEO and AI & Cybersecurity Strategist at Riskoria and a board member for the Croatian AI Association, says that this kind of content is “a gold mine for training generative models,” but you have limited power over how that image is integrated into their training strategy.

Plus, you are uploading much more than just an image of yourself. Vazdar reminds us that we are handing over “an entire bundle of metadata.” This includes the EXIF data attached to the image, such as exactly when and where the photo was taken. And your photo may have more content in it than you imagine, with the background – including people, landmarks, and objects – also able to be tied to that time and place.

In addition to this, OpenAI also collects data about the device that you are using to engage with the platform, and, according to Vazdar, “There’s also behavioral data, such as what you typed, what kind of image you asked for, how you interacted with the interface and the frequency of those actions.”

After all that, OpenAI knows a lot about you, and soon, so could their AI model, because it is studying you.

How OpenAI Uses Your Data

OpenAI claims that they did not orchestrate these social media trends simply to get training data for their AI, and that’s almost certainly true. But they also aren’t denying that access to that freely uploaded data is a bonus. As Vazdar points out, “This trend, whether by design or a convenient opportunity, is providing the company with massive volumes of fresh, high-quality facial data from diverse age groups, ethnicities, and geographies.”

OpenAI isn’t the only company using your data to train its AI. Meta recently updated its privacy policy to allow the company to use your personal information on Meta-related services, such as Facebook, Instagram, and WhatsApp, to train its AI. While it is possible to opt-out, Meta isn’t advertising that fact or making it easy, which means that most users are sharing their data by default.

You can also control what happens with your data when using ChatGPT. Again, while not well publicized, you can use ChatGPT’s self-service tools to access, export, and delete your personal information, and opt out of having your content used to improve OpenAI’s model. Nevertheless, even if you choose these options, it is still worth it to strip data like location and time from images before uploading them and to consider the privacy of any images, including people and objects in the background, before sharing.

Are Data Protection Laws Keeping Up?

OpenAI and Meta need to provide these kinds of opt-outs due to data protection laws, such as GDPR in the EU and the UK. GDPR gives you the right to access or delete your data, and the use of biometric data requires your explicit consent. However, your photo only becomes biometric data when it is processed using a specific technical measure that allows for the unique identification of an individual.

But just because ChatGPT is not using this technology, doesn’t mean that ChatGPT can’t learn a lot about you from your images.

AI and Ethics Concerns

But you might wonder, “Isn’t it a good thing that AI is being trained using a diverse range of photos?” After all, there have been widespread reports in the past of AI struggling to recognize black faces because they have been trained mostly on white faces. Similarly, there have been reports of bias within AI due to the information it receives. Doesn’t sharing from a wide range of users help combat that? Yes, but there is so much more that could be done with that data without your knowledge or consent.

One of the biggest risks is that the data can be manipulated for marketing purposes, not just to get you to buy products, but also potentially to manipulate behavior. Take, for instance, the Cambridge Analytica scandal, which saw AI used to manipulate voters and the proliferation of deepfakes sharing false news.

Vazdar believes that AI should be used to promote human freedom and autonomy, not threaten it. It should be something that benefits humanity in the broadest possible sense, and not just those with the power to develop and profit from AI.

Responsible Artificial Intelligence

OPIT’s Master’s in Responsible AI combines technical expertise with a focus on the ethical implications of AI, diving into questions such as this one. Focusing on real-world applications, the course considers sustainable AI, environmental impact, ethical considerations, and social responsibility.

Completed over three or four 13-week terms, it starts with a foundation in technical artificial intelligence and then moves on to advanced AI applications. Students finish with a Capstone project, which sees them apply what they have learned to real-world problems.

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