

Imagine that you own a business that has thousands of customers. You have data on every one of these customers, ranging from basic contact information to data about their purchasing habits. What you have is a huge dataset, and you want to extract information from that dataset in the form of patterns and insights with which you can make decisions.
You’d need a data scientist.
Data scientists specialize in shining a spotlight on the most important insights found in large datasets. They use a range of tools – from complex algorithms to artificial intelligence – to make that spotlight shine brighter. And in a world of Big Data, the data scientist’s role is more important now than ever. With these six courses, split between beginner, intermediate, and advanced levels, you put yourself in a prime position to become the data scientist that so many companies need.
Best Data Science Tutorials for Beginners
Everybody has to start somewhere, and these data science beginner tutorial options are the ideal first step on your journey into the field.
Data Science Tutorial for Beginners (Java T Point)
If you’re looking for a succinct explanation of what data science is, what it involves, and how it applies in the modern world, Java T Point’s tutorial answers the key questions. It’s structured as a long-form article rather than a set of modules or lessons, but it’s well-organized and covers all of the key points in enough depth to make it a handy primer for the data science novice.
This data science tutorial covers a range of topics, from basic explanations of the components of data science to descriptions of the types of jobs available for those who enter the field. It also digs into some of the machine learning aspects of data science, such as decision trees, so you can see how AI ties into modern data science practices.
Granted, the fact that it’s not a traditional course means there’s no community underpinning the tutorial or certification for completion. But as a primer that gives you some foundational knowledge, it’s a superb starting point.
Data Science Full Course – Learn Data Science in 10 Hours (Edureka)
Offered via YouTube, this data science tutorial makes the lofty claim of being able to teach you all you need to know about the subject in 10 hours. While that isn’t strictly true (the more complex aspects are covered superficially), it’s still a great primer for those looking to build a solid foundation in the subject.
The tutorial is a great choice for visual learners, and it covers topics like data categorization, statistics, and the data lifecycle. Charts, graphs, and other visual learning tools abound, with the constant narration helping you to understand what you’re seeing on screen.
As a full 10-hour video, the tutorial could do with being broken up into separate lessons to make it easier to keep your place. But as long as you’re happy to record time stamps (or don’t mind the full 10 hours in one sitting), the course delivers plenty of useful information.
Best Data Science Tutorials for Intermediate Learners
After completing a few of the best data science tutorials for beginners, you’re ready to get your feet wet with intermediate courses that dig into the coding that underpins data science.
Data Science with Python Tutorial (Geeksforgeeks)
Python is the programming language of choice for data scientists, as evidenced by the fact that 69% of data scientists report using Python daily. It’s no surprise, either, as Python is an extremely flexible language that’s ideal for creating the algorithms needed in data science due to its vast range of libraries. The challenge you face is twofold – figuring out how to code in Python and understanding what libraries you need to confront common data science challenges.
Geeksforgeeks offers a data science tutorial that confronts both of those challenges and helps you see how Python applies to the data science field in a practical sense. Starting with a brief introduction to the data science field (the beginner-level tutorials in this list offer more depth), it then dives into everything you need to know about Python. You’ll learn about the basics of Python, such as functions and control statements, before moving into how you can use the language for visualizing data and creating machine learning models.
It’s a highly specialized tutorial, though it’s one that’s essential for prospective data scientists, given the popularity of Python in the field. Unfortunately, there’s no certification for completion. However, it’ll equip you with so much Python knowledge that you can feel confident moving into a more advanced study without worrying about your coding chops.
Data Science and Machine Learning Essentials (Microsoft via Udemy)
Like the above course, Microsoft’s offering covers Python, albeit in far less depth. However, it stands out because it also covers a couple of other languages used commonly in data science – namely R and Azure Machine Learning. As a result, the course is an excellent choice for intermediate data scientists who want to get to grips with the main three programming languages they’ll likely use in the field.
It’s a five-week course, with Microsoft recommending between three and four hours of learning per week, and it’s delivered in English. Each weekly module is capped with a quiz that tests your knowledge. The modules cover everything from data science basics to creating machine learning models in Azure Machine Learning.
Of course, the biggest benefit of this course (aside from the content) is the Microsoft-approved certification you get at the end. Any employer who sees Microsoft on your CV will sit up and take notice. Still, you’ll need to build on what you learn here with a more advanced data science tutorial, ideally one that covers more real-world applications of working with data.
Best Data Science Tutorials for Advanced Learners
Once you’re secure in your foundational knowledge and you have a good idea of how to apply data science practices, you’re ready to step into a more advanced data science tutorial. Here are two options.
Data Science Tutorial – Learn Data Science From Scratch (DataFlair)
Think of DataFlair’s main data science tutorial page as a hub world in a video game. There are dozens of different directions in which to take your studying, and you’re in complete control of where you go and what you learn. The page hosts over 370 tutorials (free of charge) that cover everything from the basics of data science to using data mining and Python to parse through massive data sets.
The sheer depth of coverage makes this set of tutorials ideal for the advanced learner. The more basic sides of the course can fill in any knowledge gaps that weren’t covered in previous tutorials you’ve taken. And on the more advanced side, you’ll be exposed to real-world examples that show you how to apply your theoretical knowledge in a practical environment. There’s even a set of quizzes that you can use to test your understanding of what you read.
There are some drawbacks, namely that this data science tutorial doesn’t offer a certificate and is less interactive than many paid courses. However, self-paced learners who thrive when presented with pages of theoretical knowledge will find almost everything they need to know about data science in this collection.
MicroMasters® Program in Statistics and Data Science (Massachusetts Institute of Technology)
By the time you’re at the advanced stage of learning data science, you’ll probably want an official certification to take pride of place on your CV. This mini-Master’s degree comes from the Massachusetts Institute of Technology (MIT), which is one of the world’s leading technology and engineering schools.
The course lasts for one year and two months, with between 10 and 14 hours of study required per week, making it a choice only for those who can commit to a part-time consistent learning schedule. It’s also not a free data science tutorial, as you’ll have to pay £1,210 (approx. €1,401) for the program.
If you can vault those hurdles, you get a graduate-level course that teaches you how to develop the machine learning models used in modern data science. Plus, having the letters “MIT” on your course certification (and the networking opportunities that come with learning from some of the institutions leading professors) makes this course even more valuable.
Find the Best Data Science Tutorials for Your Skill Level
Whether you’re taking your first tentative steps into the world of data science or you’re an advanced learner looking to brush up your skills, there’s a data science tutorial out there for you. The six highlighted in this article represent the best data science tutorials available (two for each skill level) on the web.
Let’s close by answering a key question – why complete one of these tutorials?
Precedence Research has the answer, stating that the data science field will enjoy a compound annual growth rate (CAGR) of 16.43% between 2022 and 2030. Rapid growth means more job opportunities (and higher salaries) for those with data science skills. Use these tutorials to build your skill base before shifting your career focus to a field that looks set to explode as Big Data becomes more crucial to how companies operate.
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During the Open Institute of Technology’s (OPIT) 2025 graduation day, the OPIT team interviewed graduating student Irene about her experience with the MSc in Applied Data Science and AI. The interview focused on how Irene juggled working full-time with her study commitments and the value of the final Capstone project, which is part of all OPIT’s master’s programs.
Irene, a senior developer at ReActive, said she chose to study at OPIT to update her skills for the current and future job market.
OPIT’s MSc in Applied Data Science and AI
In her interview, Irene said she appreciated how OPIT’s course did not focus purely on the hard mathematics behind technologies such as AI and cloud computing, but also on how these technologies can be applied to real business challenges.
She said she appreciated how the course gave her the skills to explain to stakeholders with limited technical knowledge how technology can be leveraged to solve business problems, but it also equipped her to engage with technical teams using their language and jargon. These skills help graduates bridge the gap between management and technology to drive innovation and transformation.
Irene chose to continue working full-time while studying and appreciated how her course advisor helped her plan her study workload around her work commitments “down to the minute” so that she never missed a deadline or was overcome by excessive stress.
She said she would recommend the program to people at any stage in their career who want to adapt to the current job market. She also praised the international nature of the program, in terms of both the faculty and the cohort, as working beyond borders promises to be another major business trend in the coming years.
Capstone Project
Irene described the most fulfilling part of the program as the final Capstone project, which allowed her to apply what she had learned to a real-life challenge.
The Capstone Project and Dissertation, also called the MSc Thesis, is a significant project aimed at consolidating skills acquired during the program through a long-term research project.
Students, with the help of an OPIT supervisor, develop and realize a project proposal as part of the final term of their master’s journey, investigating methodological and practical aspects in program domains. Internships with industrial partners to deliver the project are encouraged and facilitated by OPIT’s staff.
The Capstone project allows students to demonstrate their mastery of their field and the skills they’ve learned when talking to employers as part of the hiring process.
Capstone Project: AI Meets Art
Irene’s Capstone project, “Call Me VasarAI: An AI-Powered Framework for Artwork Recognition and Storytelling,” focused on using AI to bridge the gap between art and artificial intelligence over time, enhancing meaning through contextualization. She developed an AI-powered platform that allows users to upload a work of art and discover the style (e.g. Expressionism), the name of the artist, and a description of the artwork within an art historical context.
Irene commented on how her supervisor helped her fine-tune her ideas into a stronger project and offered continuous guidance throughout the process with weekly progress updates. After defending her thesis in January, she noted how the examiners did not just assess her work but guided her on what could be next.
Other Example Capstone Projects
Irene’s success is just one example of a completed OPIT Capstone project. Below are further examples of both successful projects and projects currently underway.
Elina delivered her Capstone project on predictive modeling of natural disasters using data science and machine learning techniques to analyze global trends in natural disasters and their relationships with climate change-related and socio-economic factors.
According to Elina: “This hands-on experience has reinforced my theoretical and practical abilities in data science and AI. I appreciate the versatility of these skills, which are valuable across many domains. This project has been challenging yet rewarding, showcasing the real-world impact of my academic learning and the interdisciplinary nature of data science and AI.”
For his Capstone project, Musa worked on finding the optimal pipeline to fine-tune a language learning model (LLM) based on the specific language and model, considering EU laws on technological topics such as GDPR, DSA, DME, and the AI Act, which are translated into several languages.
Musa stated: “This Capstone project topic aligns perfectly with my initial interests when applying to OPIT. I am deeply committed to developing a pipeline in the field of EU law, an area that has not been extensively explored yet.”
Tamas worked with industry partner Solergy on his Capstone project, working with generative AI to supercharge lead generation, boost SEO performance, and deliver data-driven marketing insights in the realm of renewable energy.
OPIT’s Master’s Courses
All of OPIT’s master’s courses include a final Capstone project to be completed over one 13-week term in the 90 ECTS program and over two terms in the 120 ECTS program.
The MSc in Digital Business and Innovation is designed for professionals who want to drive digital innovation in both established companies and new digital-native contexts. It covers digital business foundations and the applications of new technologies in business contexts. It emphasizes the use of AI to drive innovation and covers digital entrepreneurship, digital product management, and growth hacking.
The MSc in Responsible Artificial Intelligence combines technical expertise with a focus on the ethical implications of modern AI. It focuses on real-world applications in areas like natural language processing and industry automation, with a focus on sustainable AI systems and environmental impact.
The MSc in Enterprise Cybersecurity prepares students to fulfill the market need for versatile cybersecurity solutions, emphasizing hands-on experience and soft-skills development.
The MSc in Applied Data Science and AI focuses on the intersection between management and technology. It covers the underlying fundamentals, methodologies and tools needed to solve real-life business problems that can be approached using data science and AI.

In May 2025, Greta Maiocchi, Head of Marketing and Administration at the Open Institute of Technology (OPIT), went online with Stefania Tabi, OPIT Career Services Counselor, to discuss how OPIT helps students translate their studies into a career.
You can access OPIT Career Services throughout your course of study to help with making the transition from student to professional. Stefania specifically discussed what companies and businesses are looking for and how OPIT Career Services can help you stand out and find a desirable career with your degree.
What Companies Want
OPIT degrees are tailored to a wide range of individuals, with bachelor’s degrees for those looking to establish a career and master’s degrees for experienced professionals hoping to elevate their skills to meet the current market demand.
OPIT’s degrees establish the foundation of the key technological skills that are set to reshape industries shortly, in particular artificial intelligence (AI), big data, cloud computing, and cybersecurity.
Stefania shared how companies recruiting tech talent are looking for three types of skills:
- Builders – These are the superstars of the industry today, capable of developing the technologies that will transform the industry. These roles include AI engineers, cloud architects, and web developers.
- Protectors – Cybercrime is expected to cost the world $10.5 trillion by the end of 2025, which means companies place a high value on cybersecurity professionals capable of protecting their investment, data, and intellectual property (IP).
- Decoders – Industry is producing more data than ever before, with global data storage projected to exceed 200 zettabytes this year. Businesses seek professionals who can extract value from that data, such as data scientists and data strategists.
Growing Demand
Stefania also shared statistics about the growing demand for these roles. According to the World Economic Forum, there will be a 30-35% greater demand for roles such as data analysts and scientists, big data specialists, business intelligence analysts, data engineers, and database and network professionals by 2027.
The U.S. Bureau of Labor Statistics, meanwhile, predicts that by 2032, the demand for information security will increase by 33.8%, by 21.5% for software developers, by 10.4% for computer network architects, and by 9.9% for computer system analysts. Finally, the McKinsey Global Institute predicts a similar 15-25% increase in demand for technology professionals in the business services sector.
How Career Support Makes a Difference
Next, Stefania explained that while learning essential skills is vital to accessing this growing job market, high demand does not guarantee entry. Today, professionals looking for jobs in the technology field must stand out from the hundreds of applicants for each position with high-level skills.
Applicants demonstrate technical expertise in relevant fields by completing OPIT’s courses. They also need to prove that they can deliver results, demonstrating not just what they know but how they have applied what they know to transform or benefit a business. Professionals also need adaptability, adaptive problem-solving skills, and a commitment to continuous learning. OPIT’s final Capstone projects can be an excellent way to demonstrate the value of newly acquired skills.
Each OPIT program prepares students for future careers by providing dedicated support and academic guidance at every step.
What Kind of Support Does Career Services Offer?
Career Services is specifically focused on assisting students in making the transition to the job market, and you can make an appointment with them at any time during your studies. Stefania gave some specific examples of how Career Services can support students on their journey into the career market.
Stefania said she begins by talking with students and discussing what they truly value to help them discover the type of career that aligns with their strengths. With students who are still undecided on how to start to build their careers, she helps them craft a tailored job and internship search plan.
Stefania has also worked with students who want to stand out during the job application process among the hundreds of applicants. This includes hands-on help in reframing resumes, tailoring LinkedIn profiles, and developing cover letters that tell a unique story.
Finally, Stefania has assisted students in preparing for interviews, helping them research the company, develop intelligent questions about the role to ask the interviewer and engage in mock interviews with an experienced recruiter.
Connecting With Employers
OPIT Career Services also offers students exposure to a wide range of employers and the opportunity to build relationships through masterclasses, career talks, and industry roundtables. The office also helps students build career-ready skills through interactive, hands-on workshops and hosts virtual career fairs with top recruiters.
Career Services also plays an integral role in connecting students with companies for their Capstone project in the final phase of their master’s program. So far, students have worked with companies including Sintica, Cosmica, Cisco, PayPal, Morgan Stanley, AWS, Dylog, and Accenture. Projects have included developing predictive modeling for natural disasters and fine-tuning AI to answer questions about EU tech laws in multiple languages.
What Kinds of Jobs Have OPIT Graduates Secured?
Stefania capped off her talk by sharing some of the positions that OPIT graduates have now fulfilled, including:
- Chief Information Security Officer at MOMO for MTN mobile services in Nigeria
- Data Analyst at ISX Financial in Cyprus
- Head of Sustainability Office at Banca Popolare di Sondrio in Italy
- Data Analyst at Numisma Group in Cyprus
- Senior Software Engineer at Neaform in Italy
OPIT Courses
OPIT offers both foundational bachelor’s degrees and advanced master’s courses, which are both accessible with any bachelor’s degree (it does not have to be in the field of computer science).
Choose between a BSc in Modern Computer Science for a strong technical base or a BSc in Digital Business to focus on applications.
Meanwhile, courses that involve a final Capstone project include an MSc in Applied Data Science and AI, Digital Business and Innovation, Enterprise Cybersecurity, and Responsible Artificial Intelligence.
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