

You could say that data science is the driving force behind our modern world. Digital technologies are responsible for how we work, play, and socialize, and data science impacts all those areas. This field deals with how computer systems work, learn, and connect through networks. As such, the demand for data science advancements keeps growing.
Unsurprisingly, industries worldwide require more and more data science experts. Many job openings call for people with advanced degrees – a basic knowledge of data science is no longer a considerable advantage in the job market.
Today, getting a master’s degree in data science represents a surefire way to start a lucrative career. These degrees pave the way towards better-paid jobs and higher positions. Best of all, you can get an MSc data science online.
The advantage of an online master’s degree data science program is its convenience and opportunities. You can get a prestigious degree from your home, without having additional complications of moving to campus. Plus, the degree you obtain may come from a leading university, gaining you even more favorable credentials.
Let’s look at the best online data science master’s programs and what they have to offer.
Criteria for Ranking
Finding a quality program for MSc data science online requires a detailed examination according to several criteria. When creating our list, we considered the following in particular:
- University reputation and accreditation
- The content of the courses and program curriculum
- Online program accessibility and flexibility
- Available resources and student support
- Pricing and financial aid options
- Career prospects for graduates
Top Online Master Degrees in Data Science
1. Rome Business School – International Online Master in Data Science
Program Overview
The program consists of three modules. The first focuses on managerial and leadership skills based on data. The second module deals mostly with IT and data science solutions as they apply to business problem-solving.
The third module explores how your competency in data science technology reflects on data governance. The skills you’ll learn here apply to data management through specific methods and processes.
Key Features and Highlights
The International Online Master in Data Science provides the opportunity to participate in bootcamps worldwide. The locations include the U.S., Spain, Italy, and Nigeria.
Students also have the opportunity to work on real-life cases and datasets. This kind of hands-on experience will prepare you for the professional application of your data science knowledge.
Admission Requirements and Process
The admission process for this program will consist of four steps: credential evaluation, confirmation of your application, the interview, and, finally, admission.
Since the program offers introductory classes, previous knowledge of data science isn’t a strict requirement. However, experience in particular topics will count as an advantage in your evaluation.
Cost and Financial Aid Options
Participating in this program costs €6,700. The Rome Business School offers several payment options. First, students can pay in six installments after enrolling. The installments are interest-free.
Next, paying the installments before starting the course makes you eligible for a 5% discount. Finally, paying the entire sum before enrollment comes with a 10% discount.
Scholarships are also available for this program and will be determined according to the applicant’s motivation, experience, and personal profile. Eligible applicants may choose from seven scholarship types.
Career Prospects for Graduates
The program allows students to connect with industry-leading companies, learning from the best while creating meaningful connections. The Rome Business School offers a career service with soft skills, individual coaching, and other training.
2. European Leadership University – Professional Master in Data Science & Leadership
Program Overview
As a data science program with a particular focus on leadership, this program focuses on combining the two disciplines. In other words, learners become more competent as leaders through data science skills.
The program lasts for 19 months, including data skills like machine learning, Python programming, and NLP. On the leadership side, the courses teach coaching, communication, accountability, and similar skills.
Key Features and Highlights
The faculty team at the European Leadership University consists of respected academics and experts who actively practice data science. Besides the proven industry experts and their knowledge and guidance, this program has a notable distinction: it offers two certificates and a data science MSc degree.
The first certificate you’ll receive is in data science after nine months of study. The next is the certificate in leadership and action research, which will become available after month 14. Lastly, doing the final project will award you the MSc degree.
Admission Requirements and Process
The prerequisites for this program include a Computer Science or related undergraduate degree, statistics and programming knowledge, and proven experience in IT.
Candidates who meet these requirements will go through a four-stage application process. You’ll need to submit your application online, pass an analytical test, submit your diploma, and, finally, complete the entry test.
Cost and Financial Aid Options
The program costs €5,000. There are three payment options: installments, early bird, and a flexible plan. Installments are a straightforward option and may be paid during the study period. The early bird bonus refers to paying upfront, which makes you eligible for a 10% discount.
The flexible plan is particularly interesting. It includes a membership fee, paid monthly over a longer period. In addition to the tuition cost, there’s also a €250 registration fee that you don’t have to pay until you’ve been accepted.
Career Prospects for Graduates
The university and its programs have international accreditation, which means the degree you get here will be recognized worldwide. The institution also offers mentoring services and a talent accelerator program, intended to prepare learners for high-profile jobs.
3. European School of Data Science & Technology – MSc Data Science
Program Overview
The MSc Data Science program from the European School of Data Science & Technology is a comprehensive course focused on gaining a detailed knowledge of various data science aspects. Particular attention is devoted to programming, statistics, and machine learning.
The program has 12 courses across four semesters, with each course lasting for three weeks. The semesters are organized around particular subjects concerning data science: foundation, analytics and tools, visualization and application, and experiential learning, which contains the master thesis.
Key Features and Highlights
The curriculum for this program was created according to the latest requirements and trends in the industry. Expert teachers offer one-on-one mentoring throughout each course. The program is structured to provide relevant knowledge that you can apply immediately.
Admission Requirements and Process
To enlist in the European School of Data Science & Technology (ESDST) MSc Data Science online program, you’ll need a Bachelor’s degree. However, the degree doesn’t have to be in data science or a related discipline. Lacking a degree, you can also apply for the program if you have more than three years of relevant work experience.
Since the course is in English, you’ll need proof of proficiency with sufficient scores on IELTS, PTE, TOEFL, or another accepted test. Upon the review of your application, you’ll have an interview after which you’ll be notified of whether you’re accepted or not.
Cost and Financial Aid Options
This MSc program costs €490 per month plus the registration fee of €1,500. You can pay the program fee in monthly installments or cover the entire cost (program and registration fee) at once for a 5% discount. Additional options are to pay the entire program fee for a €1,000 reduction, or pay €4,000 initially and cover the rest in 12 monthly installments of €1,500.
It’s worth mentioning that the ESDST offers several scholarships to students who meet specific standards. The scholarships may cover from 25% to 50% of the program fee.
Career Prospects for Graduates
Besides the theoretical knowledge, this program offers plenty of practice in data science, exposing students to all facets of this discipline. The experience from the projects you do during the courses will represent an advantage in the job market. In addition, you’ll be paired with a mentor from a specific industry who can provide further career assistance.
4. University of Glasgow – Data Analytics MSc
Program Overview
The Data Analytics MSc from the University of Glasgow is a three-year program. It consists of 11 core courses and two electives. The first two years follow a pace of two courses per trimester, while the final year consists of the final project and an MSc dissertation.
The program is part-time and covers all crucial facets of data science, including analytics, machine learning, programming, and predictive modeling.
Key Features and Highlights
Renowned international experts and academics teach the courses. The part-time structure allows learners to maintain a job while studying with full freedom in setting their pace. This data analytics MSc also has a fast-track option, letting you obtain the degree in two instead of three years.
Admission Requirements and Process
To enter this program, you’ll need a Bachelor’s degree equivalent to the UK upper second class, which means a GPA of 4.0-4.5. The degree doesn’t need to be from data science or statistics, but it should include mathematics on a higher level.
Alternatively, you may substitute the degree with relevant experience in data analytics or a related field. The application for the program is done entirely online.
Cost and Financial Aid Options
The total cost of the program is £15,000 or about €17,200. Additional fees may apply during the program, but only in specific cases like applying for a dissertation reassessment. Students can apply for a UK scholarship or a country-specific loan if you’re from the UK.
Career Prospects for Graduates
This MSc program creates opportunities in particular data science fields like finance, medical research, statistics, and pharmaceutics. University of Glasgow graduates reportedly boast an enviable track record in terms of employment.
5. University of Europe for Applied Sciences – Data Science MSc
Program Overview
Built with flexibility in mind, this online master degree data science program offers two, three, or four-semester options. These award 60, 90, and 120 ECTS points, respectively. All variants include courses on data analytics, engineering, and science, while the three and four-semester programs also have data visualization and marketing analytics.
Key Features and Highlights
In addition to detailed knowledge of data science, the program teaches other crucial skills, particularly in the first semester. During that time, you’ll obtain advanced English skills, learn the foundations of programming and the Office suite, and get familiar with scientific writing.
Admission Requirements and Process
You’ll need to have completed a Bachelor’s program (not necessarily in data science) to apply to this MSc. A basic grasp of programming will also be required, although a preparatory course is available if you lack any programming experience.
The admission process will consist of an entry exam and an online interview.
Cost and Financial Aid Options
Tuition fees for EU students are expressed in monthly values: €820 per month for any curriculum. Non-EU students will pay a €10,938 yearly fee. A 15% or larger discount is applicable for early applicants. Additionally, scholarship may be available on a case-by-case basis.
Career Prospects for Graduates
The University of Europe for Applied Sciences collaborates with European, multinational, and global partners. This collaboration opens up career paths for students, including actual projects and internships with leading companies like Daimler and BASF.
Tips for Choosing the Right Online MSc Data Science Program
Choosing an MSc data science online program will require careful consideration. Here’s what you should take into account to ensure you’ve enrolled in the right program:
- Whether the program aligns with your career goals
- Flexibility and time requirement
- Faculty quality and the curriculum
- The reputation and accreditation of the university
- Fees and available financial aid
Enroll in the Best Online Data Science Master’s Program
Once you gain an MSc in data science, your job opportunities will increase. The demand for new experts in the market is always high, with those holding relevant degrees having the upper edge. If you’re certain that a career in data science is right for you, don’t hesitate to complete an MSc in one of the leading institutions in the field.
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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.

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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