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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Master the AI Era: Key Skills for Success
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 24, 2025 6 min read

The world is rapidly changing. New technologies such as artificial intelligence (AI) are transforming our lives and work, redefining the definition of “essential office skills.”

So what essential skills do today’s workers need to thrive in a business world undergoing a major digital transformation? It’s a question that Alan Lerner, director at Toptal and lecturer at the Open Institute of Technology (OPIT), addressed in his recent online masterclass.

In a broad overview of the new office landscape, Lerner shares the essential skills leaders need to manage – including artificial intelligence – to keep abreast of trends.

Here are eight essential capabilities business leaders in the AI era need, according to Lerner, which he also detailed in OPIT’s recent Master’s in Digital Business and Innovation webinar.

An Adapting Professional Environment

Lerner started his discussion by quoting naturalist Charles Darwin.

“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change.”

The quote serves to highlight the level of change that we are currently seeing in the professional world, said Lerner.

According to the World Economic Forum’s The Future of Jobs Report 2025, over the next five years 22% of the labor market will be affected by structural change – including job creation and destruction – and much of that change will be enabled by new technologies such as AI and robotics. They expect the displacement of 92 million existing jobs and the creation of 170 million new jobs by 2030.

While there will be significant growth in frontline jobs – such as delivery drivers, construction workers, and care workers – the fastest-growing jobs will be tech-related roles, including big data specialists, FinTech engineers, and AI and machine learning specialists, while the greatest decline will be in clerical and secretarial roles. The report also predicts that most workers can anticipate that 39% of their existing skill set will be transformed or outdated in five years.

Lerner also highlighted key findings in the Accenture Life Trends 2025 Report, which explores behaviors and attitudes related to business, technology, and social shifts. The report noted five key trends:

  • Cost of Hesitation – People are becoming more wary of the information they receive online.
  • The Parent Trap – Parents and governments are increasingly concerned with helping the younger generation shape a safe relationship with digital technology.
  • Impatience Economy – People are looking for quick solutions over traditional methods to achieve their health and financial goals.
  • The Dignity of Work – Employees desire to feel inspired, to be entrusted with agency, and to achieve a work-life balance.
  • Social Rewilding – People seek to disconnect and focus on satisfying activities and meaningful interactions.

These are consumer and employee demands representing opportunities for change in the modern business landscape.

Key Capabilities for the AI Era

Businesses are using a variety of strategies to adapt, though not always strategically. According to McClean & Company’s HR Trends Report 2025, 42% of respondents said they are currently implementing AI solutions, but only 7% have a documented AI implementation strategy.

This approach reflects the newness of the technology, with many still unsure of the best way to leverage AI, but also feeling the pressure to adopt and adapt, experiment, and fail forward.

So, what skills do leaders need to lead in an environment with both transformation and uncertainty? Lerner highlighted eight essential capabilities, independent of technology.

Capability 1: Manage Complexity

Leaders need to be able to solve problems and make decisions under fast-changing conditions. This requires:

  • Being able to look at and understand organizations as complex social-technical systems
  • Keeping a continuous eye on change and adopting an “outside-in” vision of their organization
  • Moving fast and fixing things faster
  • Embracing digital literacy and technological capabilities

Capability 2: Leverage Networks

Leaders need to develop networks systematically to achieve organizational goals because it is no longer possible to work within silos. Leaders should:

  • Use networks to gain insights into complex problems
  • Create networks to enhance influence
  • Treat networks as mutually rewarding relationships
  • Develop a robust profile that can be adapted for different networks

Capability 3: Think and Act “Global”

Leaders should benchmark using global best practices but adapt them to local challenges and the needs of their organization. This requires:

  • Identifying what great companies are achieving and seeking data to understand underlying patterns
  • Developing perspectives to craft global strategies that incorporate regional and local tactics
  • Learning how to navigate culturally complex and nuanced business solutions

Capability 4: Inspire Engagement

Leaders must foster a culture that creates meaningful connections between employees and organizational values. This means:

  • Understanding individual values and needs
  • Shaping projects and assignments to meet different values and needs
  • Fostering an inclusive work environment with plenty of psychological safety
  • Developing meaningful conversations and both providing and receiving feedback
  • Sharing advice and asking for help when needed

Capability 5: Communicate Strategically

Leaders should develop crisp, clear messaging adaptable to various audiences and focus on active listening. Achieving this involves:

  • Creating their communication style and finding their unique voice
  • Developing storytelling skills
  • Utilizing a data-centric and fact-based approach to communication
  • Continual practice and asking for feedback

Capability 6: Foster Innovation

Leaders should collaborate with experts to build a reliable innovation process and a creative environment where new ideas thrive. Essential steps include:

  • Developing or enhancing structures that best support innovation
  • Documenting and refreshing innovation systems, processes, and practices
  • Encouraging people to discover new ways of working
  • Aiming to think outside the box and develop a growth mindset
  • Trying to be as “tech-savvy” as possible

Capability 7: Cultivate Learning Agility

Leaders should always seek out and learn new things and not be afraid to ask questions. This involves:

  • Adopting a lifelong learning mindset
  • Seeking opportunities to discover new approaches and skills
  • Enhancing problem-solving skills
  • Reviewing both successful and unsuccessful case studies

Capability 8: Develop Personal Adaptability

Leaders should be focused on being effective when facing uncertainty and adapting to change with vigor. Therefore, leaders should:

  • Be flexible about their approach to facing challenging situations
  • Build resilience by effectively managing stress, time, and energy
  • Recognize when past approaches do not work in current situations
  • Learn from and capitalize on mistakes

Curiosity and Adaptability

With the eight key capabilities in mind, Lerner suggests that curiosity and adaptability are the key skills that everyone needs to thrive in the current environment.

He also advocates for lifelong learning and teaches several key courses at OPIT which can lead to a Bachelor’s Degree in Digital Business.

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Lessons From History: How Fraud Tactics From the 18th Century Still Impact Us Today
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 17, 2025 6 min read

Many people treat cyber threats and digital fraud as a new phenomenon that only appeared with the development of the internet. But fraud – intentional deceit to manipulate a victim – has always existed; it is just the tools that have changed.

In a recent online course for the Open Institute of Technology (OPIT), AI & Cybersecurity Strategist Tom Vazdar, chair of OPIT’s Master’s Degree in Enterprise Cybersecurity, demonstrated the striking parallels between some of the famous fraud cases of the 18th century and modern cyber fraud.

Why does the history of fraud matter?

Primarily because the psychology and fraud tactics have remained consistent over the centuries. While cybersecurity is a tool that can combat modern digital fraud threats, no defense strategy will be successful without addressing the underlying psychology and tactics.

These historical fraud cases Vazdar addresses offer valuable lessons for current and future cybersecurity approaches.

The South Sea Bubble (1720)

The South Sea Bubble was one of the first stock market crashes in history. While it may not have had the same far-reaching consequences as the Black Thursday crash of 1929 or the 2008 crash, it shows how fraud can lead to stock market bubbles and advantages for insider traders.

The South Sea Company was a British company that emerged to monopolize trade with the Spanish colonies in South America. The company promised investors significant returns but provided no evidence of its activities. This saw the stock prices grow from £100 to £1,000 in a matter of months, then crash when the company’s weakness was revealed.

Many people lost a significant amount of money, including Sir Isaac Newton, prompting the statement, “I can calculate the movement of the stars, but not the madness of men.

Investors often have no way to verify a company’s claim, making stock markets a fertile ground for manipulation and fraud since their inception. When one party has more information than another, it creates the opportunity for fraud. This can be seen today in Ponzi schemes, tech stock bubbles driven by manipulative media coverage, and initial cryptocurrency offerings.

The Diamond Necklace Affair (1784-1785)

The Diamond Necklace Affair is an infamous incident of fraud linked to the French Revolution. An early example of identity theft, it also demonstrates that the harm caused by such a crime can go far beyond financial.

A French aristocrat named Jeanne de la Mont convinced Cardinal Louis-René-Édouard, Prince de Rohan into thinking that he was buying a valuable diamond necklace on behalf of Queen Marie Antoinette. De la Mont forged letters from the queen and even had someone impersonate her for a meeting, all while convincing the cardinal of the need for secrecy. The cardinal overlooked several questionable issues because he believed he would gain political benefit from the transaction.

When the scheme finally exposed, it damaged Marie Antoinette’s reputation, despite her lack of involvement in the deception. The story reinforced the public perception of her as a frivolous aristocrat living off the labor of the people. This contributed to the overall resentment of the aristocracy that erupted in the French Revolution and likely played a role in Marie Antoinette’s death. Had she not been seen as frivolous, she might have been allowed to live after her husband’s death.

Today, impersonation scams work in similar ways. For example, a fraudster might forge communication from a CEO to convince employees to release funds or take some other action. The risk of this is only increasing with improved technology such as deepfakes.

Spanish Prisoner Scam (Late 1700s)

The Spanish Prisoner Scam will probably sound very familiar to anyone who received a “Nigerian prince” email in the early 2000s.

Victims received letters from a “wealthy Spanish prisoner” who needed their help to access his fortune. If they sent money to facilitate his escape and travel, he would reward them with greater riches when he regained his fortune. This was only one of many similar scams in the 1700s, often involving follow-up requests for additional payments before the scammer disappeared.

While the “Nigerian prince” scam received enough publicity that it became almost unbelievable that people could fall for it, if done well, these can be psychologically sophisticated scams. The stories play on people’s emotions, get them invested in the person, and enamor them with the idea of being someone helpful and important. A compelling narrative can diminish someone’s critical thinking and cause them to ignore red flags.

Today, these scams are more likely to take the form of inheritance fraud or a lottery scam, where, again, a person has to pay an advance fee to unlock a much bigger reward, playing on the common desire for easy money.

Evolution of Fraud

These examples make it clear that fraud is nothing new and that effective tactics have thrived over the centuries. Technology simply opens up new opportunities for fraud.

While 18th-century scammers had to rely on face-to-face contact and fraudulent letters, in the 19th century they could leverage the telegraph for “urgent” communication and newspaper ads to reach broader audiences. In the 20th century, there were telephones and television ads. Today, there are email, social media, and deepfakes, with new technologies emerging daily.

Rather than quack doctors offering miracle cures, we see online health scams selling diet pills and antiaging products. Rather than impersonating real people, we see fake social media accounts and catfishing. Fraudulent sites convince people to enter their bank details rather than asking them to send money. The anonymity of the digital world protects perpetrators.

But despite the technology changing, the underlying psychology that makes scams successful remains the same:

  • Greed and the desire for easy money
  • Fear of missing out and the belief that a response is urgent
  • Social pressure to “keep up with the Joneses” and the “Bandwagon Effect”
  • Trust in authority without verification

Therefore, the best protection against scams remains the same: critical thinking and skepticism, not technology.

Responding to Fraud

In conclusion, Vazdar shared a series of steps that people should take to protect themselves against fraud:

  • Think before you click.
  • Beware of secrecy and urgency.
  • Verify identities.
  • If it seems too good to be true, be skeptical.
  • Use available security tools.

Those security tools have changed over time and will continue to change, but the underlying steps for identifying and preventing fraud remain the same.

For more insights from Vazdar and other experts in the field, consider enrolling in highly specialized and comprehensive programs like OPIT’s Enterprise Security Master’s program.

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