It can often feel like a computer has a “brain,” especially given modern machines’ abilities to run complex calculations and handle instructions. But all of those machines need people behind them to program algorithms and help them to learn based on explicit instructions. That’s where machine learning comes in.
This branch of artificial intelligence brings a machine’s “brain” closer to the real thing than ever before. It’s all about teaching the machine how to do more than simply execute, as machine learning is all about making a machine “think” (based on instructions and algorithms) so it can improve over time. That ability to “think” is crucial in modern business because it gives companies the ability to analyze patterns – both operational and consumer-based – enabling them to make smarter decisions.
But these businesses need people who understand how to create machine learning models. That’s where you come in. With the right machine learning tutorial under your belt, you set yourself up for a career in a field that has only just started to show glimpses of its potential.
The Best Machine Learning Tutorials
Finding the best online tutorial for machine learning isn’t easy given the sheer volume of options available. Analyzing each one based on what it teaches (and how useful it will be to your career) takes time, though you can save yourself that time by checking out the three tutorials highlighted here.
Tutorial 1 – Intro to Machine Learning (Kaggle)
As tempting as it may be to run before you can walk, you need an introduction to the basic concepts of machine learning prior to focusing on more practical applications. Enter Kaggle’s machine learning tutorial. This seven-lesson course takes about three hours of self-guided learning to complete and will leave you with a solid grounding in machine learning that you can take into more industry-focused courses.
The majority of the seven lessons – barring the first – is split into two parts. First comes a tutorial where you’ll learn about the concepts that the lesson introduces, with the second part being an exercise that tests your new skills. Along the way, you’ll learn the basics of how machine learning models work and why you need them to explore large datasets. Other lessons focus on building and validating a model, with the later lessons introducing more complex algorithms, such as random forests, and giving you a chance to test your skills in competitions.
Though this is a beginner-focused tutorial, you’ll need a solid understanding of Python before making a start. Without experience in this programming language, you’ll feel like you’re truly lost in a random forest before you ever get to learn what that term actually means. On the plus side, the tutorial has an active discussion community (which includes the course instructor Dan Becker) that can help you along and point you in the direction of other courses that supplement this one.
Tutorial 2 – Making Developers Awesome at Machine Learning (Machine Learning Mastery)
This machine learning tutorial is less a structured course and more a series of articles and step-by-step instructional lessons that take you from the foundations of machine learning to more advanced concepts. That method of breaking the course into multiple stages is ideal for students of all experience levels. Complete beginners can start with the “Foundations” level and work their way up while those with more experience can dip into specific subjects that give them trouble or will build on their existing skills.
The course is split into four sections – Foundations, Beginner, Intermediate, and Advanced. At the Foundations level, you’ll learn about the statistical concepts and models that underpin machine learning, giving you a solid basis to move into the Python programming taught in the Beginner section. Once you have a grasp of Python, the Intermediate section teaches you about deep learning and how to code machine learning algorithms. By the time you hit the Advanced stage, you’ll be working on complex subjects like computer vision and natural language processing.
With its less structured nature, this tutorial is great for people who want to dip in and out and those who need to hone in on a specific aspect of machine learning. It’s also a good choice for beginners because it covers practically everything you’ll need to know. Unfortunately, the lack of structure means you don’t get an official certification from the tutorial. Some students may also not like the “hub” nature of the tutorial, as it links you to tons of different web pages that can lead to confusion over time.
Tutorial 3 – Machine Learning Crash Course With TensorFlow APIs (Google)
If you already have a mathematical foundation (as well as some basic understanding of machine learning), Google’s tutorial helps you take your skills to the next level. You’ll need to understand algebra, statistics, and basic trigonometry, in addition to having some understanding of Python, to get started. But assuming you have all of that, this machine learning tutorial exposes you to real-world examples of the technology in action.
It’s a 25-lesson course that contains 30 exercises covering topics like model development and testing, data representation, and building neural networks. According to Google, it takes about 15 hours of self-guided study to complete, though your time may vary depending on how much you already know before you start the course.
The biggest advantage of this tutorial is the name attached to it. Google is a major player in the tech industry and the presence of its name on your CV instantly shows employers that you know your stuff. The course material is also delivered by lecturers who work at or for Google, allowing them to bring their real-world experiences into their lessons. On the downside, the tutorial’s prerequisites make it unsuitable for beginners, though Google does offer more basic courses (both in machine learning and Python) to help you build the required foundation.
Factors to Consider When Choosing a Machine Learning Tutorial
The three options presented above all make a solid case for the best online tutorial for machine learning, though each offers something different based on your current skill level. To make the best choice between the three (and any other tutorials you find) you should consider these factors before committing yourself.
Your Current Skill Level
Diving into neural networks before you even know how machine learning works is like trying to row upstream without a paddle. You’re going to get stuck in rough waters and the end result won’t be what you want it to be. Be honest with yourself about your current skill level to ensure you don’t start a tutorial that’s too difficult (or too simple) for your abilities.
Programming Languages
There’s no getting away from the fact that you’ll need to feel comfortable with programming before taking a machine learning tutorial. Specifically, you’re likely to need some knowledge of Python, though how much depends on the course you take. Other languages can help, at least in the sense of ensuring you’re familiar with programming, but you need to check the language the course uses before starting.
Specific Topics
Though the basic idea of building a machine “brain” is simple enough to understand, the machine learning waters run deep. There are tons of topics and potential specializations you could study, and not all are useful for your intended career path. Check what the course covers and ensure those topics align with what you hope to achieve once you’ve completed the tutorial.
Time Commitment
If a tutorial takes an hour or two to complete, you don’t really need to worry about how you’ll fit it around your other commitments. But if it takes you down a machine learning rabbit hole (i.e., the Machine Learning Mastery Course), you need to get serious with scheduling. Figure out how much time you can commit to your course per week and choose a tutorial that fits around your commitments.
The Cost
On the plus side, many machine learning tutorials are available free of charge. But if you’re looking for more official certification, or you want to take a more formal course, you’ll usually have to pay for the privilege. Weigh up the course’s cost against the benefit you get out of the backend.
Tips for Getting the Most Out of a Machine Learning Tutorial
Anybody can start a machine learning tutorial, but only the truly committed will complete and actually get the most out of the materials. Follow these tips to ensure you’re spending your time wisely on the tutorial you choose:
- Set clear goals from the outset that define what you want to achieve with the tutorial and where it’s supposed to lead you.
- Dedicate time to learning every week because regularity is the key to making the information you absorb stick in your mind.
- Engage with any communities related to your tutorial to learn from your peers and ask questions about the tutorial’s content.
- Apply what you learn to real-world problems, either via the course itself or by searching for examples of what you’ve learned being put into action.
- Update your knowledge and skills regularly with further tutorials because what you learn today may be out of date tomorrow.
Find the Best Online Tutorial for Machine Learning for You
There is no single “best” machine learning tutorial on the web because each approaches the subject differently. Some assume you have no knowledge at all and will start with basics before moving you into deeper subjects. Others require you to understand the computing concepts (mathematical and programmatical) that underpin machine learning before you can get started. Understand what the course offers, and what it needs from you, before you get started.
Regardless of your choice, getting started is the most important thing you can do. Once you’ve chosen a tutorial, commit yourself to it fully to take your first step (or potentially a giant leap) into a career that’s only going to grow as machine learning models become more common in business.
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More and more students are turning to careers in computer science, and it’s easy to see why. The world is becoming increasingly reliant on and powered by modern technology with every passing day.
Emerging innovations like artificial intelligence (AI) and cloud computing are set to change the face of countless industries. This means qualifications in computer science unlock the doors to countless job opportunities.
However, this is also a dynamic and rapidly changing field – a field that demands a distinct set of core skills to not only achieve success, but also future-proof your career for years to come.
The Importance and Value of Computer Science and Cloud Computing Qualifications
Official statistics show that the European cloud computing market is set to experience an astonishing compound annual growth rate (CAGR) of almost 23% in the coming years, moving from a value of €110 billion in 2024 to a lower-end estimate €250 billion by 2028, and it won’t stop there.
The same sort of growth is being seen across the full spectrum of computer science fields and industries, with emerging technologies like AI, automation, and edge computing all spearheading the surging value and importance of these sectors.
The increasing shift away from conventional computing towards cloud computing shows just how quickly the technological world changes and evolves. It also demonstrates the need for professionals with a wide and varied range of skills, plus the ability to adapt to rapidly changing situations.
Those who can bring these skills to the table, supported by a comprehensive education and effective computer science qualifications, can enjoy:
- Entry into job markets that have exceptionally high levels of demand.
- Diverse career opportunities in fields that range from AI and machine learning to computer engineering and software development.
- Competitive salaries, with consistently high rates offered all around the world.
- Job security and stability, given the ever-increasing significance of technology in the modern world.
Core Skills to Master for Long Careers in Computer Science
Next, let’s look into the actual specific skills that computer science students and aspiring leaders will need to master to secure their futures.
Programming Languages
Being able to work with code is the bedrock of almost any career in computer science. Aspiring scientists will need to master one or several programming languages, including Java for building business and web apps, Python for web development, and C++ for system programming.
Networks and Architectures
Computer scientists also need a strong core knowledge of the fundamentals of the computing world, like how networks function, the various protocols and architectures that control the flow of data from device to device, etc.
Algorithms and Data
Algorithms play a fundamental role in fields like AI and machine learning, so computer scientists must understand how different algorithms and data structures drive computing processes, problem-solving, and development.
Software Development
Computer scientists may spend much of their time working on development projects post-graduation, which may include apps for the web, business, mobile, and more. A strong understanding of the stages of the software development lifecycle and processes involved is, therefore, essential.
Cloud Computing
With cloud computing growing in importance, unlocking whole new fields, like software as a service (SaaS) and desktop as a service (DaaS), the computer scientists of tomorrow will also need to have intricate knowledge of how cloud computing works and the potential it holds.
Soft Skills
Along with the many technical skills listed above, computer scientists will also benefit from vital soft skills that will help them when collaborating with others, presenting their ideas, driving innovation in their chosen fields, leading teams, and managing projects. These skills include:
- Being able to communicate effectively, both with fellow computer scientists and non-technical audiences as well
- Analytical thinking and problem-solving skills that help scientists understand and respond to challenges
- Adaptability, so that scientists can keep on learning, evolving their skill sets, and embracing new tech and ideas as they emerge
- The ability to work as part of a team, often fundamental for large-scale computing projects
- Attention to detail that allows you to spot that single line of code that needs fixing, or for tasks like debugging and data interpretation
Get the Best Start With a BSc in Computer Science at OPIT
We’ve seen the skills you need to succeed in computer science and cloud computing for years to come, but one question remains: where is the best place to gain these skills and acquire the necessary knowledge for genuine long-term success?
The answer: the Open Institute of Technology (OPIT).
An exclusively online learning platform specializing in computer science and digital business, OPIT offers a curated collection of online degrees for tomorrow’s technology leaders, including a Foundation Program for beginners, bachelor’s programs, and master’s degrees for the most experienced students.
Why Study at OPIT?
Advantages of studying with OPIT include:
- Accessible and flexible online learning to suit your needs and pace
- A focus on real-world applications of the skills and knowledge imparted
- A leading team of top tutors and professors from diverse fields and nations
- An international community of students with which to collaborate
- Progressive assessment of skills and knowledge, as opposed to exam-heavy schedules
Those planning pathways into computer science and cloud computing are best served by OPIT’s BSc in Computer Science program.
Lasting six terms and worth 180 ECTS credits, this fully remote, online, and accredited undergraduate degree was developed with insights from industry leaders, academics, and employers within the IT industry.
It equips graduates with both the fundamental theoretical knowledge they need to succeed in technology, as well as the practical skills required to enter the world of work and immediately innovate in fields like programming, cybersecurity, data science, AI, and cloud computing.
Like other courses and programs available at OPIT, this BSc in Computer Science provides students with a flexible learning program involving a mixture of recorded and engaging live content, progressive assessment, fast-track options for those who study at a faster pace, and round-the-clock accessibility to tutors and fellow learners.
If you feel that computer science or cloud computing is the right path for you, and you want to secure the foundational skills you need to succeed, consider the OPIT BSc in Computer Science to help you achieve your dreams.
On September 8, 2025, the Open Institute of Technology (OPIT) officially inaugurated its 2025/26 academic year, welcoming a whole host of new students into the institute, ready to gain the skills and knowledge they need to be the tech industry leaders of tomorrow.
Faculty members, guest speakers from around the world, and hundreds of students from over 100 nations were all in attendance at the online inauguration event. Among them was one new student on the MSc in Responsible AI program: Rem Lampa, also known by his online alias, Kuya Dev.
A Filipino podcaster, speaker, and developer, Kuya Dev documented the inauguration experience in a YouTube video, sharing his thoughts on the event. Here’s a detailed look at his experience, showing the welcoming and effective way in which new OPIT students are brought into the institute from the first day.
An Overview of the Inauguration Event
The latest OPIT inauguration event was one to remember, with the institute celebrating several notable milestones. These included the first graduation of the MSc in Applied Data Science and AI program, and the unveiling of new industry connections and corporate partners offering opportunities for graduates.
Various guest speakers were in attendance, including the former Italian Minister of Education and current OPIT Rector, Professor Francesco Profumo, plus the CEO of Malta’s accreditation authority MFHEA, Dr. Rose Anne Cuschieri.
OPIT founder, Riccardo Ocleppo, also took to the stage to highlight the transformative role of education and the unique possibilities offered by the online-only OPIT degrees, stating:
“When we launched OPIT in 2022, we wanted to prove that an online degree could be rigorous, international, deeply connected to the world of work, and engaging. Three years later, we can already see results. This year alone, 300 new students are joining us, representing 98 nationalities.”
Those hundreds of new students were also, naturally, in attendance for their big inauguration day, welcomed into the institute’s various BSc and MSc programs in specialties like Computer Science, Digital Business, Digital Business and Innovation, and Cybersecurity.
Introducing Rem ‘Kuya Dev’ Lampa
As mentioned, one of the new students joining was vlogger and podcaster, Kuya Dev.
Already boasting extensive experience and technical expertise in the computing world, Kuya Dev has founded several tech communities, including Tech Career Shifter Philippines and Server-Side JavaScript.
He describes himself as an advocate for responsible AI and tech practices, and once gave a powerful TEDx talk about the negative potential impacts of artificial intelligence (AI), including its large carbon footprint and involving exploitation of workers in emerging nations. So, it was only fitting that he signed up for OPIT’s MSc in Responsible AI.
The MSc in Responsible AI Program
A postgraduate program lasting three or four terms (between 12 and 24 months, total), OPIT’s MSc in Responsible AI is an accredited program that combines technical skills with a core focus on the ethical implications of AI technology.
It explores real-world use cases of AI and ways in which this exciting and powerful technology can be used responsibly and sustainably, emphasizing its potential for both positive and negative change in areas such as the environment and society as a whole.
Students of this program enjoy all the usual benefits that come with studying at OPIT, like flexible-paced learning, tutors available on a daily basis, a dynamic and engaging online learning environment, and fair, progressive assessments over time.
Those who graduate can move into careers in AI Application Development, AI Research, and AI Business Consulting.
Highlights and Impressions of Kuya Dev’s Inauguration Experience
Inauguration is always a special moment in any student’s academic journey as they take their first tentative yet exciting steps towards new knowledge and skills that can unlock their potential and accelerate their development.
It can even be a “make-or-break” moment in which students can either feel welcomed, empowered, and eager to begin their studies, or, conversely, experience feelings of worry, doubt, or regret if the inauguration lacks the spark they were hoping to feel.
Fortunately, Kuya Dev and his many fellow new OPIT students had a very positive experience at the inauguration event, with the vlogger calling it both “very fruitful” and “very insightful.” Some of the specific highlights he mentioned included:
An International Community
Early in the inauguration event, Kuya Dev heard from Professor Francesco Profumo about how OPIT was welcoming students from over 90 countries.
This, for Kuya Dev and for so many other students, is one of the big perks of studying with OPIT. It allows students to meet, engage, and exchange with people from dozens of different backgrounds, cultures, and communities, learning new ways of thinking and collaborating.
Real World Applications
The OPIT inauguration also focused on another of the university’s key features: a focus not merely on imparting knowledge to students or making them memorize facts, figures, and theorems, but actually teaching them how to apply that knowledge and ideas to real-world uses.
Kuya Dev commented on how other universities that he had considered attending appeared more conventional and limited in their approach, and also shared his excitement and enthusiasm at OPIT’s unique approach, focusing more on genuine industry collaboration and real-life scenarios.
Inspiring Speakers
The vlogger and podcaster also commented on the various key speakers who hosted the event. He was pleased to see that they were not only academically oriented but also all had real-world experience and a diverse range of working backgrounds in fields like politics.
This, too, is part of what makes OPIT different. It features a winning team of international tutors, professors, and experts from diverse fields, including the aforementioned former Italian Education Minister, education executives, research chairs, digital content creation specialists, and more.
Graduate Experiences
Finally, Kuya Dev noted how several OPIT graduates spoke to those about to follow the same path they did, including students from nations as diverse as the U.S., Italy, and Nigeria.
They all shared their experiences and detailed what they enjoyed most about studying with OPIT, including key factors such as professors who took the time to get to know their students, as well as the depth of the topics and knowledge covered in each course.
A Successful First Step Into OPIT Education
All in all, the recent inauguration event was a major success for all involved, giving students like Kuya Dev the ideal introduction to life and study with OPIT. He, like so many of his new fellow students, left the event eager and excited to expand their knowledge and broaden their horizons in unique ways that only OPIT can provide.
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