Technology transforms the world in so many ways. Ford’s introduction of the assembly line was essential to the vehicle manufacturing process. The introduction of the internet changed how we communicate, do business, and interact with the world. And in machine learning, we have an emerging technology that transforms how we use computers to complete complex tasks.
Think of machine learning models as “brains” that machines use to actively learn. No longer constrained by rules laid out in their programming, machines have the ability to develop an understanding of new concepts and deliver analysis in ways they never could before. And as a prospective machine learning student, you can become the person who creates the “brains” that modern machines use now and in the future.
But you need a good starting point before you can do any of that. This article covers three of the best machine learning tutorials for beginners who want to get their feet wet while building foundational knowledge that serves them in more specialized courses.
Factors to Consider When Choosing a Machine Learning Tutorial
A machine learning beginner can’t expect to jump straight into a course that delves into neural networking and deep learning and have any idea what they’re doing. They need to learn to crawl before they can walk, making the following factors crucial to consider when choosing a machine learning tutorial for beginners.
- Content quality. You wouldn’t use cheap plastic parts to build an airplane, just like you can’t rely on poor-quality course content to get you started with machine learning. Always look for reviews of a tutorial before engaging, in addition to checking the credentials of the provider to ensure they deliver relevant content that aligns with your career goals.
- Instructor expertise. Sticking with our airplane analogy, imagine being taught how to pilot a plane by somebody who’s never actually flown. It simply wouldn’t work. The same goes for a machine learning tutorial, as you need to see evidence that your instructor does more than parrot information that you can find elsewhere. Look for real-world experience and accreditation from recognized authorities.
- Course structure and pacing. As nice as it would be to have an infinite amount of free time to dedicate to learning, that isn’t a reality for anybody. You have work, life, family, and possibly other study commitments to keep on top of, and your machine learning tutorial has to fit around all of it.
- Practical and real-world examples. Theoretical knowledge can only take you so far. You need to know how to apply what you’ve learned, which is why a good tutorial should have practical elements that test your knowledge. Think of it like driving a car. You can read pages upon pages of material on how to drive properly but you won’t be able to get on the road until you’ve spent time learning behind the wheel.
- Community support. Machine learning is a complex subject and it’s natural to feel a little lost with the materials in many tutorials. A strong community gives you a resource base to lean into, in addition to exposing you to peers (and experienced tech-heads) who can help you along or point you in the right career direction.
Top Three Machine Learning Tutorials for Beginners
Now you know what to look for in a machine learning tutorial for beginners, you’re ready to start searching for a course. But if you want to take a shortcut and jump straight into learning, these three courses are superb starting points.
Tutorial 1 – Intro to Machine Learning (Kaggle)
Offered at no cost, Intro to Machine Learning is a three-hour self-paced course that allows you to learn as and when you feel like learning. All of which is helped by Kaggle’s clever save system. You can use it to save your progress and jump back into your learning whenever you’re ready. The course has seven lessons, the first of which offers an introduction to machine learning as a concept. Whereas the other six dig into more complex topics and come with an exercise for you to complete.
Those little exercises are the tutorial’s biggest plus point. They force you to apply what you’ve learned before you can move on to the next lesson. The course also has a dedicated community (led by tutorial creator Dan Becker) that can help you if you get stuck. You even get a certificate for completing the tutorial, though this certificate isn’t as prestigious as one that comes from an organization like Google or IBM.
On the downside, the course isn’t a complete beginner’s course. You’ll need a solid understanding of Python before you get started. Those new to coding should look for Python courses first or they’ll feel lost when the tutorial starts throwing out terminology and programming libraries that they need to use.
Ideal for students with experience in Python who want to apply the programming language to machine learning models.
Tutorial 2 – What Is Machine Learning? (Udemy)
You can’t build a house without any bricks and you can’t build a machine learning model before you understand the different types of learning that underpin that model. Those different types of learning are what the What is Machine Learning tutorial covers. You’ll get to grips with supervised, unsupervised, and reinforcement learning, which are the three core learning types a machine can use to feed its “brain.”
The course introduces you to real-world problems and helps you to see which type of machine learning is best suited to solving those problems. It’s delivered via online videos, totaling just under two hours of teaching, and includes demonstrations in Python to show you how each type of learning is applied to real-world models. All the resources used for the tutorial are available on a GitHub page (which also gives you access to a strong online community) and the tutorial is delivered by an instructor with over 27 years of experience in the field.
It’s not the perfect course, by any means, as it focuses primarily on learning types without digging much deeper. Those looking for a more in-depth understanding of the algorithms used in machine learning won’t find it here, though they will build foundational knowledge that helps them to better understand those algorithms once they encounter them. As an Udemy course, it’s free to take but requires a subscription to the service if you want a certificate and the ability to communicate directly with the course provider.
Ideal for students who want to learn about the different types of machine learning and how to use Python to apply them.
Tutorial 3 – Machine Learning Tutorial (Geeksforgeeks)
As the most in-depth machine learning tutorial for beginners, the Geeksforgeeks offering covers almost all of the theory you could ever hope to learn. It runs the gamut from a basic introduction to machine learning through to advanced concepts, such as natural language processing and neural networks. And it’s all presented via a single web page that acts like a hub that links you to many other pages, allowing you to tailor your learning experience based on what aligns best with your goals.
The sheer volume of content on offer is the tutorial’s biggest advantage, with dedicated learners able to take themselves from complete machine learning newbies to accomplished experts if they complete everything. There’s also a handy discussion board that puts you in touch with others taking the course. Plus, the “Practice” section of the tutorial includes real-world problems, including a “Problem of the Day” that you can use to test different skills.
However, some students may find the way the material is presented to be a little disorganized and it’s easy to lose track of where you are among the sea of materials. The lack of testing (barring the two or three projects in the “Practice” section) may also rankle with those who want to be able to track their progress easily.
Ideal for self-paced learners who want to be able to pick and choose what they learn and when they learn it.
Additional Resources for Learning Machine Learning
Beyond tutorials, there are tons of additional resources you can use to supplement your learning. These resources are essential for continuing your education because machine learning is an evolving concept that changes constantly.
- Books. Machine learning books are great for digging deeper into the theory you learn via a tutorial, though they come with the downside of offering no practical examples or ways to interact with authors.
- YouTube channels. YouTube videos are ideal for visual learners and they tend to offer a free way to build on what you learn in a tutorial. Examples of great channels to check out include Sentdex and DeepLearningAI, with both channels covering emerging trends in the field alongside lectures and tutorials.
- Blogs and websites. Blogs come with the advantage of the communities that sprout up around them, which you can rely on to build connections and further your knowledge. Of course, there’s the information shared in the blogs, too, though you must check the writer’s credentials before digging too deep into their content.
Master a Machine Learning Tutorial for Beginners Before Moving On
A machine learning tutorial for beginners can give you a solid base in the fundamentals of an extremely complex subject. With that base established, you can build up by taking other courses and tutorials that focus on more specialized aspects of machine learning. Without the base, you’ll find the learning experience much harder. Think of it like building a house – you can’t lay any bricks until you have a foundation in place.
The three tutorials highlighted here give you the base you need (and more besides), but it’s continued study that’s the key to success for machine learning students. Once you’ve completed a tutorial, look for books, blogs, YouTube channels, and other courses that help you keep your knowledge up-to-date and relevant in an ever-evolving subject.
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From the same author
Read the articleDuring 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.
Read the articleIn 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.
-
Go to all authors
Related posts
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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