Data analytics is a science that is all about taking raw datasets and translating them into insights that you (or others) can use. Think of it as the conduit between the reams of data an organization collects and the management team. As a data analyst, you’re the person who makes sense of the numbers so management can take action.

At least, that’s how data analytics works in a business context. Switch to the research side of things and you’ll play a crucial role in interpreting the results of complex experiments by helping researchers understand the factors that lead to their results and the effects of changes they make.

Getting your start in this field usually requires you to complete a BSc in computer science with data analytics. This article looks at five of the best options provided by some of the world’s top universities.

Top BSc Degrees in Computer Science With Data Analytics Programs

In creating our list of the five best BSc computer science with data analytics programs, we considered the following criteria:

  • Reputation – A good reputation is like word of mouth for a university. We looked for institutions that have an established track record of quality courses, both in the AI field and outside of it.
  • Curriculum – Many computer science degrees have an analytics component but don’t focus on it as a specialization. The courses we chose put data analytics in the spotlight.
  • Faculty Expertise – Who wants to learn from people who don’t have solid reputations in the data analytics industry? The people who teach you are as important (perhaps even more important) as the content they teach.
  • Industry Connections – A good course is like a tree. The course itself is the trunk, which then branches off into all sorts of industries. You want a course with plenty of branches (i.e., many paths into the industry).
  • Support and Resources – Data analytics isn’t a simple concept that you can pick up with a few hours of study. It’s like a vast ocean and it’s easy to get lost. The right support and resources are like a compass that keeps the student on track.

Top Programs

With the above criteria in mind, we’ve collected five great BSc computer science with data analytics programs for you to consider.

1 – Computer Science With Pathway in Data Analytics (Middle East College)

When universities come together, the result is usually a top-notch degree that allows you to draw from global expertise. That’s what you get with Middle East College’s course, as it’s offered in conjunction with the UK’s Coventry University.

It’s an eight-semester course that focuses on data collection, codification, and treatment, with as much importance placed on practical application as on academic theory. Entry requirements are strict and require:

  • A General Education Certificate (GEC) or similar
  • Either a General Foundation Programme (GFP) certificate or a passing grade in the university-administered MEC placement test
    • Scoring 60% or above in each component of the MEC is a must if you want to use it to replace a GFP.

The big selling point for this course is the link to Coventry University, which has been among the top 15 universities in the UK for over half a decade. That link also creates career opportunities, with the Middle East College faculty exposing you to Asian opportunities while Coventry University can provide a route into the UK for international students.

2 – Bachelor of Science in Data Science and Analytics (St. Ambrose University)

Ranked as the top data analytics program in the world by Bachelor Studies, St. Ambrose’s course is a four-year degree that offers internships to some of the world’s leading companies. This internship program is so extensive that over 75% of the university’s students end up with a work placement that can provide them with a direct route into a career.

As for the course itself, you’ll develop foundational knowledge in statistics and computing before moving on to practical ways to apply that knowledge. The course also has an ethical component, which is crucial given the potentially controversial means some companies use to collect data.

International students need to achieve the equivalent of an American 2.5 out of 4.0 Grade Point Average (GPA), making this one of the easier courses to get onto. You also have to complete a Declaration of Finances form (available via the university’s website) to demonstrate proof of funding for your studies.

3 – BSc Digital Business & Data Science (University of Applied Sciences Europe)

The Hamburg-based University of Applied Sciences Europe is among the top 25 private universities in the continent and it’s a popular choice for international students. Its BSc computer science with data analytics program is interesting because it combines the fundamentals of data science with business concepts. Beyond learning advanced programming and analytics concepts, you’ll discover how those concepts apply in fields as varied as economics and cybersecurity. Throw in some marketing and entrepreneurship modules and this is an excellent choice for the prospective start-up owner.

Entry requirements are fairly simple. You’ll need proof of a high school diploma (or your country’s equivalent), which you submit alongside a CV and demonstration of English-language proficiency. A passing grade in an IELTS or TOEFL exam should do the job for the latter requirement.

Non-EU students have an extra hurdle to jump – a tuition deposit. You have to pay €3,000 upfront, which serves as a reservation fee for the course. The good news is that this fee counts toward your full tuition, so it’s deducted from the total. Think of it as paying money upfront for a restaurant reservation, with that money going toward the final bill.

4 – Data Science BSc (Warwick University)

Ranked as the 10th-best university in the UK and in the top 100 in the world, Warwick University is a good performer in terms of pure credentials. But the school’s state-of-the-art statistics department makes it stand out, with its research department being touted as “world-leading.”

Its Data Science BSc takes in plenty of the skills you’ll use in data analytics, including how to parse through massive datasets to get to crucial information. The scope of this work is particularly impressive, with the course teaching how data analytics applies in industries as varied as finance and social networks. Studying (and even working) abroad is also offered to those who want to build their networks through their studies.

Entry requirements are stringent, with students generally expected to have at least two (and usually three) A* A-Level grades, or equivalents, to get in. The university’s website digs into more specific requirements for international students. This is an English-language course, too, so you’ll need proof of your English-speaking abilities or have to pass the university’s Pre-Sessional English Course before you’re considered for entry.

5 – BSc in Data Science and Analytics (National University of Singapore)

Ranked as the 11th best university in the world by QS University Rankings, the National University of Singapore is a trailblazer in the data analytics field. To get in, you’ll need to show the equivalent of an H2 pass in mathematics or further mathematics, which is roughly equivalent to an A grade at A-Level in the UK.

The course itself is a four-year honors program that starts by teaching you the foundational analytical methods applied in data science. From there, it branches into teaching how these concepts apply in real-world scenarios before introducing you to tools and techniques you’ll use in practical work.

Experiential learning is key to the course, with the National University of Singapore calling it “industry-driven” to highlight that this is a course that teaches you how to drive the car, as well as showing you what lies under the hood. To support this approach, the university runs its “Co-operative Education Programme” which combines academic study with several internships over four years of study.

Benefits of Pursuing a BSc in Computer Science With Data Analytics

By now, you’re probably asking yourself a big question: “Why should I study a BSc in computer science with data analytics?

Reason 1 – Develop In-Depth Knowledge

A data analytics bachelor’s degree teaches you how to use the tools and techniques needed in the field. But the theory that underpins those tools, along with the programming languages you’ll use, is near-universal in terms of its usefulness. As a result, following this degree track opens up career opportunities that extend into the software programming and computing fields, as well as analytics.

Reason 2 – Enhanced Employability

Building on the previous point, the skills you develop as part of a BSc in computer science with data analytics will make you seem like the goose that lays the golden eggs to employers. You’ll have such a varied skillset that you can lend your hand to almost anything in the computing sector. Salaries are solid, too, with data analysts earning an average of €55,000 per year in Germany alone.

Reason 3 – Opportunities for Further Education

If a data analytics BSc is the equivalent of drawing up a blueprint for a house, later educational pursuits are all about building that house into something special. These courses lay the groundwork for later education (such as OPIT’s Master in Applied Data Science and AI), in addition to making it easier for you to earn professional certifications that look great on your CV.

Tips for Choosing the Right BSc Computer Science With Data Analytics Program

Right now, you’re at a crossroads that seems to branch off into an infinite number of paths. There are so many data analytics courses to choose from that it’s hard to know which way to turn. Use these tips to ensure you pick the right one:

  • Align your course selection with your career goals – if it doesn’t take you closer to where you want to be then it’s not the course for you.
  • Dig deeper into what each course offers by comparing curricula to see which courses have gaps and which cover everything you want to learn.
  • Location and general student life are important because you need to have a life outside of education, so pay attention to both.
  • The cost of tuition can often be like a brick wall to students, but research into financial aid often helps you to find the ladder that gets you over that wall.
  • If you have the opportunity, speak to faculty and alumni to discover what makes the course so special.

Keep Exploring to Find the Right Course for You

The five programs covered here are among the best BSc computer science with data analytics courses in the world, but that doesn’t necessarily mean they’re right for you. Exploration is key, as you must transform into an explorer to navigate your way toward the course that fits your needs from career, life, and passion perspectives. Make the right choices, and you’ll put yourself on course for a data-driven career that’s rewarding on both the mental and financial levels.

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Cyber Threat Landscape 2024: Human-Centric Cyber Threats
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 17, 2024 9 min read

Human-centric cyber threats have long posed a serious issue for organizations. After all, humans are often the weakest link in the cybersecurity chain. Unfortunately, when artificial intelligence came into the mix, it only made these threats even more dangerous.

So, what can be done about these cyber threats now?

That’s precisely what we asked Tom Vazdar, the chair of the Enterprise Cybersecurity Master’s program at the Open Institute of Technology (OPIT), and Venicia Solomons, aka the “Cyber Queen.”

They dedicated a significant portion of their “Cyber Threat Landscape 2024: Navigating New Risks” master class to AI-powered human-centric cyber threats. So, let’s see what these two experts have to say on the topic.

Human-Centric Cyber Threats 101

Before exploring how AI impacted human-centric cyber threats, let’s go back to the basics. What are human-centric cyber threats?

As you might conclude from the name, human-centric cyber threats are cybersecurity risks that exploit human behavior or vulnerabilities (e.g., fear). Even if you haven’t heard of the term “human-centric cyber threats,” you’ve probably heard of (or even experienced) the threats themselves.

The most common of these threats are phishing attacks, which rely on deceptive emails to trick users into revealing confidential information (or clicking on malicious links). The result? Stolen credentials, ransomware infections, and general IT chaos.

How Has AI Impacted Human-Centric Cyber Threats?

AI has infiltrated virtually every cybersecurity sector. Social engineering is no different.

As mentioned, AI has made human-centric cyber threats substantially more dangerous. How? By making them difficult to spot.

In Venicia’s words, AI has allowed “a more personalized and convincing social engineering attack.”

In terms of email phishing, malicious actors use AI to write “beautifully crafted emails,” as Tom puts it. These emails contain no grammatical errors and can mimic the sender’s writing style, making them appear more legitimate and harder to identify as fraudulent.

These highly targeted AI-powered phishing emails are no longer considered “regular” phishing attacks but spear phishing emails, which are significantly more likely to fool their targets.

Unfortunately, it doesn’t stop there.

As AI technology advances, its capabilities go far beyond crafting a simple email. Venicia warns that AI-powered voice technology can even create convincing voice messages or phone calls that sound exactly like a trusted individual, such as a colleague, supervisor, or even the CEO of the company. Obey the instructions from these phone calls, and you’ll likely put your organization in harm’s way.

How to Counter AI-Powered Human-Centric Cyber Threats

Given how advanced human-centric cyber threats have gotten, one logical question arises – how can organizations counter them? Luckily, there are several ways to do this. Some rely on technology to detect and mitigate threats. However, most of them strive to correct what caused the issue in the first place – human behavior.

Enhancing Email Security Measures

The first step in countering the most common human-centric cyber threats is a given for everyone, from individuals to organizations. You must enhance your email security measures.

Tom provides a brief overview of how you can do this.

No. 1 – you need a reliable filtering solution. For Gmail users, there’s already one such solution in place.

No. 2 – organizations should take full advantage of phishing filters. Before, only spam filters existed, so this is a major upgrade in email security.

And No. 3 – you should consider implementing DMARC (Domain-based Message Authentication, Reporting, and Conformance) to prevent email spoofing and phishing attacks.

Keeping Up With System Updates

Another “technical” move you can make to counter AI-powered human-centric cyber threats is to ensure all your systems are regularly updated. Fail to keep up with software updates and patches, and you’re looking at a strong possibility of facing zero-day attacks. Zero-day attacks are particularly dangerous because they exploit vulnerabilities that are unknown to the software vendor, making them difficult to defend against.

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Nurturing a Culture of Skepticism

The key component of the human-centric cyber threats is, in fact, humans. That’s why they should also be the key component in countering these threats.

At an organizational level, numerous steps are needed to minimize the risks of employees falling for these threats. But it all starts with what Tom refers to as a “culture of skepticism.”

Employees should constantly be suspicious of any unsolicited emails, messages, or requests for sensitive information.

They should always ask themselves – who is sending this, and why are they doing so?

This is especially important if the correspondence comes from a seemingly trusted source. As Tom puts it, “Don’t click immediately on a link that somebody sent you because you are familiar with the name.” He labels this as the “Rule No. 1” of cybersecurity awareness.

Growing the Cybersecurity Culture

The ultra-specific culture of skepticism will help create a more security-conscious workforce. But it’s far from enough to make a fundamental change in how employees perceive (and respond to) threats. For that, you need a strong cybersecurity culture.

Tom links this culture to the corporate culture. The organization’s mission, vision, statement of purpose, and values that shape the corporate culture should also be applicable to cybersecurity. Of course, this isn’t something companies can do overnight. They must grow and nurture this culture if they are to see any meaningful results.

According to Tom, it will probably take at least 18 months before these results start to show.

During this time, organizations must work on strengthening the relationships between every department, focusing on the human resources and security sectors. These two sectors should be the ones to primarily grow the cybersecurity culture within the company, as they’re well versed in the two pillars of this culture – human behavior and cybersecurity.

However, this strong interdepartmental relationship is important for another reason.

As Tom puts it, “[As humans], we cannot do anything by ourselves. But as a collective, with the help within the organization, we can.”

Staying Educated

The world of AI and cybersecurity have one thing in common – they never sleep. The only way to keep up with these ever-evolving worlds is to stay educated.

The best practice would be to gain a solid base by completing a comprehensive program, such as OPIT’s Enterprise Cybersecurity Master’s program. Then, it’s all about continuously learning about new developments, trends, and threats in AI and cybersecurity.

Conducting Regular Training

For most people, it’s not enough to just explain how human-centric cyber threats work. They must see them in action. Especially since many people believe that phishing attacks won’t happen to them or, if they do, they simply won’t fall for them. Unfortunately, neither of these are true.

Approximately 3.4 billion phishing emails are sent each day, and millions of them successfully bypass all email authentication methods. With such high figures, developing critical thinking among the employees is the No. 1 priority. After all, humans are the first line of defense against cyber threats.

But humans must be properly trained to counter these cyber threats. This training includes the organization’s security department sending fake phishing emails to employees to test their vigilance. Venicia calls employees who fall for these emails “clickers” and adds that no one wants to be a clicker. So, they do everything in their power to avoid falling for similar attacks in the future.

However, the key to successful employee training in this area also involves avoiding sending similar fake emails. If the company keeps trying to trick the employees in the same way, they’ll likely become desensitized and less likely to take real threats seriously.

So, Tom proposes including gamification in the training. This way, the training can be more engaging and interactive, encouraging employees to actively participate and learn. Interestingly, AI can be a powerful ally here, helping create realistic scenarios and personalized learning experiences based on employee responses.

Following in the Competitors’ Footsteps

When it comes to cybersecurity, it’s crucial to be proactive rather than reactive. Even if an organization hasn’t had issues with cyberattacks, it doesn’t mean it will stay this way. So, the best course of action is to monitor what competitors are doing in this field.

However, organizations shouldn’t stop with their competitors. They should also study other real-world social engineering incidents that might give them valuable insights into the tactics used by the malicious actors.

Tom advises visiting the many open-source databases reporting on these incidents and using the data to build an internal educational program. This gives organizations a chance to learn from other people’s mistakes and potentially prevent those mistakes from happening within their ecosystem.

Stay Vigilant

It’s perfectly natural for humans to feel curiosity when it comes to new information, anxiety regarding urgent-looking emails, and trust when seeing a familiar name pop up on the screen. But in the world of cybersecurity, these basic human emotions can cause a lot of trouble. That is, at least, when humans act on them.

So, organizations must work on correcting human behaviors, not suppressing basic human emotions. By doing so, they can help employees develop a more critical mindset when interacting with digital communications. The result? A cyber-aware workforce that’s well-equipped to recognize and respond to phishing attacks and other cyber threats appropriately.

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Cyber Threat Landscape 2024: The AI Revolution in Cybersecurity
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 17, 2024 9 min read

There’s no doubt about it – artificial intelligence has revolutionized almost every aspect of modern life. Healthcare, finance, and manufacturing are just some of the sectors that have been virtually turned upside down by this powerful new force. Cybersecurity also ranks high on this list.

But as much as AI can benefit cybersecurity, it also presents new challenges. Or – to be more direct –new threats.

To understand just how serious these threats are, we’ve enlisted the help of two prominent figures in the cybersecurity world – Tom Vazdar and Venicia Solomons. Tom is the chair of the Master’s Degree in Enterprise Cybersecurity program at the Open Institute of Technology (OPIT). Venicia, better known as the “Cyber Queen,” runs a widely successful cybersecurity community looking to empower women to succeed in the industry.

Together, they held a master class titled “Cyber Threat Landscape 2024: Navigating New Risks.” In this article, you get the chance to hear all about the double-edged sword that is AI in cybersecurity.

How Can Organizations Benefit From Using AI in Cybersecurity?

As with any new invention, AI has primarily been developed to benefit people. In the case of AI, this mainly refers to enhancing efficiency, accuracy, and automation in tasks that would be challenging or impossible for people to perform alone.

However, as AI technology evolves, its potential for both positive and negative impacts becomes more apparent.

But just because the ugly side of AI has started to rear its head more dramatically, it doesn’t mean we should abandon the technology altogether. The key, according to Venicia, is in finding a balance. And according to Tom, this balance lies in treating AI the same way you would cybersecurity in general.

Keep reading to learn what this means.

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Implement a Governance Framework

In cybersecurity, there is a governance framework called ISO/IEC 27000, whose goal is to provide a systematic approach to managing sensitive company information, ensuring it remains secure. A similar framework has recently been created for AI— ISO/IEC 42001.

Now, the trouble lies in the fact that many organizations “don’t even have cybersecurity, not to speak artificial intelligence,” as Tom puts it. But the truth is that they need both if they want to have a chance at managing the risks and complexities associated with AI technology, thus only reaping its benefits.

Implement an Oversight Mechanism

Fearing the risks of AI in cybersecurity, many organizations chose to forbid the usage of this technology outright within their operations. But by doing so, they also miss out on the significant benefits AI can offer in enhancing cybersecurity defenses.

So, an all-out ban on AI isn’t a solution. A well-thought-out oversight mechanism is.

According to Tom, this control framework should dictate how and when an organization uses cybersecurity and AI and when these two fields are to come in contact. It should also answer the questions of how an organization governs AI and ensures transparency.

With both of these frameworks (governance and oversight), it’s not enough to simply implement new mechanisms. Employees should also be educated and regularly trained to uphold the principles outlined in these frameworks.

Control the AI (Not the Other Way Around!)

When it comes to relying on AI, one principle should be every organization’s guiding light. Control the AI; don’t let the AI control you.

Of course, this includes controlling how the company’s employees use AI when interacting with client data, business secrets, and other sensitive information.

Now, the thing is – people don’t like to be controlled.

But without control, things can go off the rails pretty quickly.

Tom gives just one example of this. In 2022, an improperly trained (and controlled) chatbot gave an Air Canada customer inaccurate information and a non-existing discount. As a result, the customer bought a full-price ticket. A lawsuit ensued, and in 2024, the court ruled in the customer’s favor, ordering Air Canada to pay compensation.

This case alone illustrates one thing perfectly – you must have your AI systems under control. Tom hypothesizes that the system was probably affordable and easy to implement, but it eventually cost Air Canada dearly in terms of financial and reputational damage.

How Can Organizations Protect Themselves Against AI-Driven Cyberthreats?

With well-thought-out measures in place, organizations can reap the full benefits of AI in cybersecurity without worrying about the threats. But this doesn’t make the threats disappear. Even worse, these threats are only going to get better at outsmarting the organization’s defenses.

So, what can the organizations do about these threats?

Here’s what Tom and Venicia suggest.

Fight Fire With Fire

So, AI is potentially attacking your organization’s security systems? If so, use AI to defend them. Implement your own AI-enhanced threat detection systems.

But beware – this isn’t a one-and-done solution. Tom emphasizes the importance of staying current with the latest cybersecurity threats. More importantly – make sure your systems are up to date with them.

Also, never rely on a single control system. According to our experts, “layered security measures” are the way to go.

Never Stop Learning (and Training)

When it comes to AI in cybersecurity, continuous learning and training are of utmost importance – learning for your employees and training for the AI models. It’s the only way to ensure all system aspects function properly and your employees know how to use each and every one of them.

This approach should also alleviate one of the biggest concerns regarding an increasing AI implementation. Namely, employees fear that they will lose their jobs due to AI. But the truth is, the AI systems need them just as much as they need those systems.

As Tom puts it, “You need to train the AI system so it can protect you.”

That’s why studying to be a cybersecurity professional is a smart career move.

However, you’ll want to find a program that understands the importance of AI in cybersecurity and equips you to handle it properly. Get a master’s degree in Enterprise Security from OPIT, and that’s exactly what you’ll get.

Join the Bigger Fight

When it comes to cybersecurity, transparency is key. If organizations fail to report cybersecurity incidents promptly and accurately, they not only jeopardize their own security but also that of other organizations and individuals. Transparency builds trust and allows for collaboration in addressing cybersecurity threats collectively.

So, our experts urge you to engage in information sharing and collaborative efforts with other organizations, industry groups, and governmental bodies to stay ahead of threats.

How Has AI Impacted Data Protection and Privacy?

Among the challenges presented by AI, one stands out the most – the potential impact on data privacy and protection. Why? Because there’s a growing fear that personal data might be used to train large AI models.

That’s why European policymakers sprang into action and introduced the Artificial Intelligence Act in March 2024.

This regulation, implemented by the European Parliament, aims to protect fundamental rights, democracy, the rule of law, and environmental sustainability from high-risk AI. The act is akin to the well-known General Data Protection Regulation (GDPR) passed in 2016 but exclusively targets the use of AI. The good news for those fearful of AI’s potential negative impact is that every requirement imposed by this act is backed up with heavy penalties.

But how can organizations ensure customers, clients, and partners that their data is fully protected?

According to our experts, the answer is simple – transparency, transparency, and some more transparency!

Any employed AI system must be designed in a way that doesn’t jeopardize anyone’s privacy and freedom. However, it’s not enough to just design the system in such a way. You must also ensure all the stakeholders understand this design and the system’s operation. This includes providing clear information about the data being collected, how it’s being used, and the measures in place to protect it.

Beyond their immediate group of stakeholders, organizations also must ensure that their data isn’t manipulated or used against people. Tom gives an example of what must be avoided at all costs. Let’s say a client applies for a loan in a financial institution. Under no circumstances should that institution use AI to track the client’s personal data and use it against them, resulting in a loan ban. This hypothetical scenario is a clear violation of privacy and trust.

And according to Tom, “privacy is more important than ever.” The same goes for internal ethical standards organizations must develop.

Keeping Up With Cybersecurity

Like most revolutions, AI has come in fast and left many people (and organizations) scrambling to keep up. However, those who recognize that AI isn’t going anywhere have taken steps to embrace it and fully benefit from it. They see AI for what it truly is – a fundamental shift in how we approach technology and cybersecurity.

Those individuals have also chosen to advance their knowledge in the field by completing highly specialized and comprehensive programs like OPIT’s Enterprise Cybersecurity Master’s program. Coincidentally, this is also the program where you get to hear more valuable insights from Tom Vazdar, as he has essentially developed this course.

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