

Combine mathematics with analytics, mix in programming skills, and add a dash of artificial intelligence, and you have the recipe for creating a data scientist. These professionals use complex technical skills to parse, analyze, and draw insights from complex datasets, enabling more accurate decision-making in the process.
As companies gather more data than ever before (both about their customers and themselves), these skills are in increasingly high demand. That’s demonstrated by data from the U.S. Bureau of Labor Statistics, which says that the number of data science jobs in the U.S. alone looks set to increase by 36% between 2021 and 2031.
That higher-than-average growth rate creates an opportunity for students, though grasping that opportunity requires a dedication to learning. This article explores the question of what is data science course material and highlights a selection of courses that set you on a data-propelled career path.
What to Expect From a Data Science Course
Answering the question of “what is data science course?” starts with examining the components of the typical course. Bear in mind that these components vary in nature and complexity depending on the specific course you take, though all are usually present.
Overview of Course Content
The content of a data science course is usually split into four core categories:
- Statistics and Probability – Math underpins everything a data scientist does, as they use numbers to spot patterns and determine the likelihood of various potential outcomes. Most data science courses delve into statistics and probability for this reason, with more advanced courses often requiring a degree in a field related to these areas.
- Programming – Whether it’s Python (the most popular data science programming language), R, or SQL, your course will teach you how to write in a language that machines understand.
- Data Visualization and Analysis – Anybody can collect reams of data. It’s the ability to visualize that data (and draw insights from it) that sets data scientists apart from other professionals. A good course equips you with the ability to use visualization tools to shine a spotlight on what a dataset actually tells you.
- Machine Learning and AI – The rise of machine learning transformed data science. Using algorithms created by data scientists, machines can analyze datasets presented to them and learn from the patterns to predict probabilities for different outcomes and even predict market trends. Your course will teach you how to create the algorithms that serve as a machine learning model’s “brain.”
Hands-On Projects and Real-World Applications
If you had the desire, you could read pages and pages on how to tune a car’s engine. But without practical and real-world wrench-in-hand experience working on an engine, you’ll never figure out how what you learn from books applies in the field.
The same line of thinking applies to data science, which is often so technically complex that it’s difficult to see how what you learn applies in the real world. A good data science course incorporates a real-world component through projects and exposure to faculty members who have direct experience in using the skills they teach.
Peer Collaboration and Networking
What is data science course for if not to learn how to become a data scientist? While learning the technical side is crucial, of course, a good course also puts you in contact with like-minded individuals who have the same (or similar) goals as you.
That contact helps you to build the collaborative skills you’ll need when you enter the workforce. But perhaps more importantly, it aids you in creating a network of peers who could lead you to job opportunities or work with you on entrepreneurial ventures.
Top Data Science Courses Available
With the components of a data science course established, you have a vital question to answer – what data science course should you take? The following are four suggestions (two online courses and two university courses) that give you a solid grounding in the subject.
Online Courses
Taking a data science course online gives you flexibility, though you may miss out on some of the collaborative and networking aspects that university-led courses provide.
Course 1 – What Is Data Science? (IBM via Coursera)
Coming with the stamp of approval from IBM, a leading name in the computer science field, this nine-hour course is suitable for beginners who want a self-paced learning approach. It’s part of a multi-part program (the IBM Data Science Professional Certificate) that’s designed to give you an industry-recognized qualification that could fast-track your entry into the field.
As for the course itself, it’s split into three parts, each containing multiple instructor-led videos and quizzes to test what you’ve learned. By the end, you’ll understand what data scientists do, build a basic understanding of various data science-related topics, and see how the profession relates to the modern business world. Granted, the course offers a surface-level understanding of the subject, with more complex topics examined in other classes. But it’s a superb tool for developing the foundation on which you can build with other courses.
Course 2 – Introduction to Data Science With Python (Harvard via edX)
Where IBM’s course equips you with general knowledge, Harvard’s online offering digs into the practical side of data science. Specifically, it focuses on using Python (and its many libraries) to solve data science problems drawn from real-world examples.
The course takes eight weeks, with study time between three and four hours per week. Ultimately, this class helps you build on your established programming skills and shows you how to apply them in a data science context.
As you may have guessed, that mention of building on existing skills means you’ll need a solid understanding of Python to participate in this free course. But assuming you have that, Harvard’s class is ideal for showing you just how flexible the language can be, especially when developing machine learning algorithms. Furthermore, simply having the word “Harvard” on your online certification adds credibility to your CV when you start applying for jobs.
University Programs
University programs demand a larger time (and monetary) commitment than purely online programs, though the upside is that you get a more prestigious qualification at the end. These two courses are ideal, with one even being a hybrid of online and university-level courses.
Course 1 – Master in Applied Data Science & AI (OPIT)
Let’s get the obvious out of the way first – you’ll need a BSc degree, or an equivalent, in a computer science or mathematical subject to take OPIT’s data science Master’s degree course.
Assuming you meet that prerequisite, this course comes in 18 and 12-month varieties, with the latter being a fast-tracked version that delivers the same content while asking you to dedicate more time to studying. It costs €6,500 to take, though early bird discounts are available, and an EU-accredited university delivers it.
The course eschews traditional exams by taking a progressive assessment approach to determine how well you’re absorbing the materials. It’s also focused on the practical side of things, with the application of data science in business problem-solving and communication being core modules.
Course 2 – MSc in Social Data Science (University of Oxford)
As the world’s leading university for seven consecutive years, according to Times Higher Education (THE) World University Rankings, the University of Oxford has outstanding credentials. And its MSc in Social Data Science is an interesting course to take because it specializes in a specific subject area – human behavior.
The degree stands on the precipice of an emerging field as it focuses on using data science to analyze, critique, and reevaluate existing social processes. It combines general machine learning models with more specialized data science tools, such as natural language processing and computer vision, to equip students with a high degree of technical knowledge.
That knowledge doesn’t come cheap, either in time or monetary commitment. The University of Oxford expects students to devote 40 hours per week to study, with overseas students having to pay £30,910 (approx. €35,795) to participate. While these investments are naturally intimidating, the university’s prestige makes the time and money you spend worthwhile when you start speaking to employers.
Factors to Consider When Choosing a Data Science Course
The four courses presented here each offer something different in terms of delivery and the expertise required of the student to participate. When choosing between them (and any other courses you find), you should consider the following questions:
- Does the course content and curriculum align with your career goals?
- Can you make time for the course within your schedule, and how much flexibility does it offer?
- Do the instructors provide the expertise you need and teach in a style that suits your preferred way of learning?
- Will you get an adequate return on your investment, both in terms of the prestige of the certification you receive and the knowledge you gain?
- Have past (or current) students recommended the course as a good option for prospective data scientists?
The Benefits of Completing a Data Science Course
Given the technical nature of the subject, you may be asking yourself what is data science course content going to deliver in terms of benefits to your life. The answers are as follows:
- Your skills improve your job prospects by putting you in pole position to enter a market that’s set for substantial growth over the next 10 years.
- The problem-solving and analytical tools you gain are useful in the data science field and other career paths.
- Any course you select puts you in contact with industry professionals who offer networking opportunities that could lead to a new job.
- You get to learn about (and experiment with) cutting-edge tools and technologies that will become the standard for modern business, and more, in the coming years.
What Is Data Science Course – It’s Your Route Into a Great Career
Let’s conclude by reiterating something mentioned at the start of the article – the data science sector will grow by 36% over the next decade or so.
That growth alone demonstrates the importance of data science, as well as why choosing the right course is so critical to your future success. With the right course, you make yourself a desirable candidate to organizations that are quickly accepting that they need data scientists to help them make decisions for the future.
Related posts

Source:
- Metro, published on October 09th, 2025
After ChatGPT came on the scene in 2022, the tech industry quickly began comparing the arrival of AI to the dawn of the internet in the 1990s.
Back then, dot-com whizzes were minting easy millions only for the bubble to burst in 2000 when interest rates were hiked. Investors sold off their holdings, companies went bust and people lost their jobs.
Now central bank officials are worried that the AI industry may see a similar boom and bust.
A record of the Financial Policy Committee’s October 2 meeting shows officials saying financial market evaluations of AI ‘appear stretched’.
‘This, when combined with increasing concentration within market indices, leaves equity markets particularly exposed should expectations around the impact of AI become less optimistic,’ they added.
AI-focused stocks are mainly in US markets but as so many investors across the world have bought into it, a fallout would be felt globally.
ChatGPT creator OpenAI, chip-maker Nvidia and cloud service firm Oracle are among the AI poster companies being priced big this year.
Earnings are ‘comparable to the peak of the dot-com bubble’, committee members said.
Factors like limited resources – think power-hungry data centres, utilities and software that companies are spending billions on – and the unpredictability of the world’s politics could lead to a drop in stock prices, called a ‘correction’.
In other words, the committee said, investors may be ignoring how risky AI technology is.
Metro spoke with nearly a dozen financial analysts, AI experts and stock researchers about whether AI will suffer a similar fate. There were mixed feelings.
‘Every bubble starts with a story people want to believe,’ says Dat Ngo, of the trading guide, Vetted Prop Firms.
‘In the late 90s, it was the internet. Today, it’s artificial intelligence. The parallels are hard to ignore: skyrocketing stock prices, endless hype and companies investing billions before fully proving their business models.
‘The Bank of England’s warning isn’t alarmist – it’s realistic. When too much capital chases the same dream, expectations outpace results and corrections follow.’
Dr Alessia Paccagnini, an associate Professor from the University College Dublin’s Michael Smurfit Graduate Business School, says that companies are spending £300billion annually on AI infrastructure, while shoppers are spending $12billion. That’s a big difference.
Tech firms listed in the US now represent 30% of New York’s stock index, S&P 500 Index, the highest proportion in 50 years.
‘As a worst-case scenario, if the bubble does burst, the immediate consequences would be severe – a sharp market correction could wipe trillions from stock valuations, hitting retirement accounts and pension funds hard,’ Dr Paccagnini adds.
‘In my opinion, we should be worried, but being prepared could help us avoid the worst outcomes.’
One reason a correction would be so bad is because of how tangled-up the AI world is, says George Sweeney, an investing expert at the personal finance website site Finder.
‘If it fails to meet the lofty expectations, we could see an almighty unravelling of the AI hype that spooks markets, leading to a serious correction,’ he says.
Despite scepticism, AI feels like it’s everywhere these days, from dog bowls and fridges to toothbrushes and bird feeders.
And it might continue that way for a while, even if not as enthusiastically as before, says Professor Filip Bialy, who specialises in computer science and AI ethics at the at Open Institute of Technology.
‘TAI hype – an overly optimistic view of the technological and economic potential of the current paradigm of AI – contributes to the growth of the bubble,’ he says.
‘However, the hype may end not with the burst of the bubble but rather with a more mature understanding of the technology.’
Some stock researchers worry that the AI boom could lose steam when the companies spending billions on the tech see profits dip.
The AI analytic company Qlik found that only one in 10 business say their AI initiatives are seeing sizeable returns.
Qlik’s chief strategy officer, James Fisher, says this doesn’t show that the hype for AI is bursting, ‘but how businesses look at AI is changing’.

OPIT – Open Institute of Technology offers an innovative and exciting way to learn about technology. It offers a range of bachelor’s and master’s programs, plus a Foundation Year program for those taking the first steps towards higher education. Through its blend of instruction-based and independent learning, it empowers ambitious minds with the skills and knowledge needed to succeed.
This guide covers all you need to know to join OPIT and start your educational journey.
Introducing the Open Institute of Technology
Before we dig into the nitty-gritty of the OPIT application process, here’s a brief introduction to OPIT.
OPIT is a fully accredited Higher Education Institution under the European Qualification Framework (EQF) and the MFHEA Authority. It offers exclusively online education in English to an international community of students. With a winning team of top professors and a specific focus on computer science, it trains the technology leaders of tomorrow.
Some of the unique elements that characterize OPIT’s approach include:
- No final exams. Instead, students undergo progressive assessments over time
- A job-oriented, practical focus on the courses
- 24/7 support, including AI assistance and student communities, so everyone feels supported
- A strong network of company connections, unlocking doors for graduates
Reasons to Join OPIT
There are many reasons for ambitious students and aspiring tech professionals to study with OPIT.
Firstly, since all the study takes place online, it’s a very flexible and pleasant way to learn. Students don’t feel the usual pressures or suffer the same constraints they would at a physical college or university. They can attend from anywhere, including their own homes, and study at a pace that suits them.
OPIT is also a specialist in the technology field. It only offers courses focused on tech and computer science, with a team of professors and tutors who lead the way in these topics. This ensures that students get high-caliber learning opportunities in this specific sector.
Learning at OPIT is also hands-on and applicable to real-world situations, despite taking place online. Students are not just taught core skills and knowledge, but are also shown how to apply those skills and knowledge in their future careers.
In addition, OPIT strives to make technology education as accessible, inclusive, and affordable as possible. Entry requirements are relatively relaxed, fees are fair, and students from around the world are welcome here.
What You Need to Know About Joining OPIT
Now you know why it’s worth joining OPIT, let’s take a closer look at how to go about it. The following sections will cover how to apply to OPIT, entry requirements, and fees.
The OPIT Application Process
Unsurprisingly for an online-only institution, the application process for OPIT is all online, too. Users can submit the relevant documents and information on their computers from the comfort of their homes.
- Visit the official OPIT site and click the “Apply now” button to get started, filling out the relevant forms.
- Upload your supporting documents. These can include your CV, as well as certificates to prove your past educational accomplishments and level of English.
- Take part in an interview. This should last no more than 30 minutes. It’s a chance for you to talk about your ambitions and background, and to ask questions you might have about OPIT.
That’s it. Once you complete the above steps, you will be admitted to your chosen course and can start enjoying OPIT education once the first term begins. You’ll need to sign your admissions contract and pay the relevant fees, then begin classes.
Entry Requirements for OPIT Courses
OPIT offers a small curated collection of courses, each with its own requirements. You can consult the relevant pages on the official OPIT site to find out the exact details.
For the Foundation Program, for example, you simply need an MQF/EQF Level 3 or equivalent qualification. You also need to demonstrate a minimum B2 level of English comprehension.
For the BSc in Digital Business, applicants should have a higher secondary school leaving certificate, plus B2-level English comprehension. You can also support your application with a credit transfer from previous studies or relevant work experience.
Overall, the requirements are simple, and it’s most important for applicants to be ambitious and eager to build successful careers in the world of technology. Those who are driven and committed will get the best from OPIT’s instruction.
Fees and Flexible Payments at OPIT
As mentioned above, OPIT makes technological education accessible and affordable for all. Its tuition fees cover all relevant teaching materials, and there are no hidden costs or extras. The institute also offers flexible payment options for those with different budgets.
Again, exact fees vary depending on which course you want to take, so it’s important to consult the specific info for each one. You can pay in advance to enjoy 10% off the final cost, or refer a friend to also obtain a discount.
In addition to this, OPIT offers need-based and merit-based scholarships. Successful candidates can obtain discounts of up to 40% on bachelor’s and master’s tuition fees. This can substantially bring the term cost of each program down, making OPIT education even more accessible.
Credit Transfers and Experience
Those who are entering OPIT with pre-existing work experience or relevant academic achievements can benefit from the credit transfer program. This allows you to potentially skip certain modules or even entire semesters if you already have relevant experience in those fields.
OPIT is flexible and fair in terms of recognizing prior learning. So, as long as you can prove your credentials and experience, this could be a beneficial option for you. The easiest way to find out more and get started is to email the OPIT team directly.
Join OPIT Today
Overall, the process to join OPIT is designed to be as easy and stress-free as possible. Everything from the initial application forms to the interview and admission process is straightforward. Requirements and fees are flexible, so people in different situations and from different backgrounds can get the education they want. Reach out to OPIT today to take your first steps to tech success.
Have questions?
Visit our FAQ page or get in touch with us!
Write us at +39 335 576 0263
Get in touch at hello@opit.com
Talk to one of our Study Advisors
We are international
We can speak in: