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.

Related posts

Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 14, 2025 6 min read

Source:


Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

Read the full article below (in Italian):

Read the article
The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 10, 2025 7 min read

There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

  • Where we are currently with AI and future trajectories
  • The impact AI is having on the job landscape
  • Sustainability concerns and ethical dilemmas
  • The fundamental risks associated with current AI technology

According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

  • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
  • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
  • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
  • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
  • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
  • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

Read the article