

Did you know that machines can learn, too, similarly to humans?
In machine learning, software applications can be trained to parse data, learn from it, and then make informed decisions based on their findings. This outcome prediction has proven to be invaluable in numerous industries, including IT (malware threat detection), healthcare (disease diagnosis and prognosis), manufacturing (business process automation), and finance (fraud detection).
The importance of machine learning in today’s technology-driven world can’t be understated. So, if you’re considering a career in data science, software engineering, or artificial intelligence (AI), this is the skill to learn.
Fortunately, learning this skill is now accessible to almost anyone. Just go online and find a machine learning course for beginners.
We’ve gathered our three favorites to help you narrow your search (and avoid wasting time on subpar courses). We aim to make it easy to select the perfect free machine learning course and crush it online.
Criteria for Selecting the Top Beginner-Friendly Online Picks
The internet offers seemingly endless learning resources. This is undoubtedly great news, as it levels the playing field for eager learners worldwide. But be careful; not all online resources will be valuable to you. Some will just waste your time.
So, how can you comb through the sea of content and find a course worth pursuing? By knowing precisely what you’re looking for, of course. Check out our selection criteria to track down a great online course.
Course Content and Structure
Most courses you find online will come with a description. The more detailed it is, the better. By carefully reading the description, you’ll better understand what the course covers and how it is structured.
These descriptions can sometimes read fluffy to get as many learners to apply. But try to look past the buzzwords and extract only the essential information – what the syllabus looks like, how many hours it takes to complete the course, and how the lessons are spaced.
If there are video lessons, check previews to ensure you’ll only work with high-quality video and audio outputs throughout the course.
Instructor Expertise and Teaching Style
If the course’s content is sound, it’s time to move on to the person (or people) who will present it to you. After all, anyone can read a bunch of words from a book. It takes an experienced and knowledgeable instructor to help you truly understand the learning material.
So, before signing up for the course, do a little research on the instructor. Check out their bio to learn about their expertise and experience in the field.
Beyond that, play a lecture or two to ensure their teaching style suits you. Having issues with the little things like their voice or body language can impact your concentration and, in turn, your success.
Platform Features and User Experience
Now that we’ve covered what you’re learning and who you’re learning it from, the only question is where the learning will take place.
Take a more in-depth look at the platform hosting your chosen course. Ensure it offers a seamless user experience, as glitches and downtime aren’t exactly ideal for a learning environment.
Also, the more exciting features the platform has, the easier it will be to stick to the course. Different learning material formats, interactive elements, discussion forums, and progress tracking are just some of the features that can significantly improve your learning experience.
Community Support and Resources
The lack of personal interaction in online learning can make you feel like you’re all alone. This can be incredibly challenging if you’re struggling with a lesson or a part of the course. So, when looking for the perfect online class, ensure you’ll get a chance to interact with other learners or even experts in the field.
Asking questions, sharing insights, collecting feedback, and receiving support and motivation should be a part of every learner’s journey.
Cost and Accessibility
If your chosen course checks all your boxes, don’t celebrate just yet. First, check whether you can access it and how much it costs.
Access can sometimes be limited by your country or device, so make sure nothing stands between you and learning online.
As for the cost, you’ll find plenty of high-quality courses free of charge. If there is a fee to pay, check whether you can purchase just the individual class or you have to subscribe to the platform. The latter approach is better for those who want to acquire multiple skills and work on their education long-term.
Top Beginner-Friendly Online Picks for Free Machine Learning Courses
Here are the top three beginner-friendly machine learning courses we’ve chosen based on the selection criteria above. Each one should help you learn the fundamentals of this field and how to use machine learning effectively as a skill.
Supervised Machine Learning: Regression and Classification by Andrew Ng
If you want to learn more about machine learning, why not consult one of its leading figures? That’s what you can do if you take this course. You’ll learn from Andrew Ng, a prominent computer scientist and a pioneer in machine learning and AI. All things considered, it’s no wonder this is probably the most popular free machine learning course online.
During this course, you’ll master the key concepts of machine learning (supervised and unsupervised learning and best practices) and learn how to apply them in practice. Some of the skills you’ll gain include:
- Linear regression
- Logistic regression for classification
- Gradient descent
- Regularization to avoid overfitting
This is one of the best beginner courses for entering the machine learning field. It offers abundant knowledge, a flexible schedule, and resettable deadlines. The only downside is that you must enroll in the entire specialization to receive a certificate upon completion.
Machine Learning Crash Course by Google
Google is a major disruptor in the AI industry. So, a free machine learning course offered by this tech giant is seriously a big deal. As the name suggests, this is a crash course, so expect a fast-paced and intense approach to machine learning.
Throughout 25 lessons, you’ll learn about specific machine-learning areas through video lectures from Google researchers, real-world case studies, written guides, and hands-on exercises.
The key topics this course covers include:
- A deep dive into neural networks
- The inner workings of gradient descent
- Model training and evaluation
- The importance of loss functions
The course is relatively short (15 hours) yet informative, so it can be an excellent choice for those pursuing machine learning while having a job. However, if you’re an absolute beginner, you’ll have to do some reading before starting the course, which some may view as a downside.
Practical Machine Learning With Scikit-Learn by Adam Eubanks
If you’re looking for something even shorter than Google’s Crash Course, you’ll love this course on Udemy. You’ll learn the most powerful machine-learning algorithms in a little over an hour. This course focuses on Scikit-Learn, a Python machine-learning library ideal for beginners.
Here are some of the algorithms this course covers:
- Linear regression
- Polynomial regression
- Multiple linear regression
- Logistic regression
- Support vector machines
- Decision trees
This is the perfect course for kick-starting your machine-learning journey. However, some learners might find it too limited in scope. Also, the course lacks interaction with the instructor, which might be a deal breaker for some learners.
Tips for Success in Learning Machine Learning Online
Imagine going through all the trouble of finding the perfect machine learning free online course, only to abandon it halfway through. There’s no judgment here, of course. We know how difficult it can be to persevere with learning outside the traditional classroom and school system.
So, here are some tips to help you complete a machine learning course for beginners triumphantly:
- Set clear goals and expectations. Before starting the course, remind yourself of why you’re doing it and how it fits your career development. Don’t just buy the course for the sake of buying it; these impulse purchases rarely translate to success.
- Dedicate consistent time for learning. Like with many things in life, consistency is key. But this time, there’s no one to keep you on track besides yourself. So, work on your self-discipline and commit to regular study sessions.
- Engage with the community and seek help when needed. Online learning can feel like an isolating experience. But it doesn’t have to, provided you’ve selected the right platform. If you ever feel stuck, don’t hesitate to seek help from the community. These simple interactions will help you stay motivated and focused.
- Apply learned concepts to real-world projects. As soon as you gain a fundamental understanding of machine learning, try to put this knowledge to practice. Seeing how the theory you’re learning sets you up for success is a great incentive to keep learning.
- Continuously update skills and knowledge. Are you done with the machine learning course for beginners? Great, it’s time to look for a more advanced one. Continuously learning and improving your skills is the only way to stay on top.
Considerable Knowledge at No Cost
You won’t make a mistake regardless of whether you put your trust in Andrew Ng or Adam Eubanks or go the Google route. What you will do is gain valuable knowledge about an even more valuable skill: machine learning.
If you want to master your knowledge of machine learning, consider pursuing a Bachelor’s degree in Modern Computer Science from the Open Institute of Technology. The syllabus includes two courses focusing on machine learning and numerous others that will skyrocket your career opportunities.
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Open Institute of Technology (OPIT) masterclasses bring students face-to-face with real-world business challenges. In OPIT’s July masterclass, OPIT Professor Francesco Derchi and Ph.D. candidate Robert Mario de Stefano explained the principles of regenerative businesses and how regeneration goes hand in hand with growth.
Regenerative Business Models
Professor Derchi began by explaining what exactly is meant by regenerative business models, clearly differentiating them from sustainable or circular models.
Many companies pursue sustainable business models in which they offset their negative impact by investing elsewhere. For example, businesses that are big carbon consumers will support nature regeneration projects. Circular business models are similar but are more focused on their own product chain, aiming to minimize waste by keeping products in use as long as possible through recycling. Both models essentially aim to have a “net-zero” negative impact on the environment.
Regenerative models are different because they actively aim to have a “net-positive” impact on the environment, not just offsetting their own use but actively regenerating the planet.
Massive Transformative Purpose
While regenerative business models are often associated with philanthropic endeavors, Professor Derchi explained that they do not have to be, and that investment in regeneration can be a driver of growth.
He discussed the importance of corporate purpose in the modern business space. Having a strong and clearly stated corporate purpose is considered essential to drive business decision-making, encourage employee buy-in, and promote customer loyalty.
But today, simple corporate missions, such as “make good shoes,” don’t go far enough. People are looking for a Massive Transformational Purpose (MTP) that can take the business to the next level.
Take, for example, Ben & Jerry’s. The business’s initial corporate purpose may have been to make great ice cream and serve it up in a way that people will enjoy. But the business really began to grow when they embraced an MTP. As they announced in their mission statement, “We believe that ice cream can change the world.” Their business activities also have the aim of advancing human rights and dignity, supporting social and economic justice, and protecting and restoring the Earth’s natural systems. While these aims are philanthropic, they have also helped the business grow.
RePlanet
Professor Derchi next talked about RePlanet, a business he recently worked to develop their MTP. Founded in 2015, RePlanet designs and implements customized renewable energy solutions for businesses and projects. The company already operates in the renewable energy field and ranked as the 21st fastest-growing business in Italy in 2023. So while they were already enjoying great success, Derchi worked with them to see if actively embracing a regenerative business model could unlock additional growth.
Working together, RePlanet moved towards an MTP of building a greener future based on today’s choices, ensuring a cleaner world for generations. Meeting this goal started with the energy products that RePlanet sells, such as energy systems that recover heat from dairy farms. But as the business’s MTP, it goes beyond that. RePlanet doesn’t just engage suppliers; it chooses partners that share its specific values. It also influences the projects they choose to work on – they prioritize high-impact social projects, such as recently installing photovoltaic energy systems at a local hospital in Nigeria – and how RePlanet treats its talent, acknowledging that people are the true energy of the company.
Regenerative Business Strategies
Based on work with RePlanet and other businesses, Derchi has identified six archetypal regenerative business strategies for businesses that want to have both a regenerative impact and drive growth:
- Regenerative Leadership – Laying the foundation for regeneration in a broader sense throughout the company
- Nature Regeneration – Strategies to improve the health of the natural world
- Social Regeneration – Regenerating human ecosystems through things such as fair-trade practices
- Responsible Sourcing – Empowering and strengthening suppliers and their communities
- Health & Well-being – Creating products and services that have a positive effect on customers
- Employee Focus – Improve work conditions, lives, and well-being of employees.
Case Studies
Building on the concept of regenerative business models, Roberto Mario de Stefano shared other case studies of businesses that are having a positive impact and enjoying growth thanks to regenerative business models and strategies.
Biorfarm
Biorfarm is a digital platform that supports small-scale agriculture by creating a direct link between small farmers and consumers. Cutting out the middleman in modern supply chains means that farmers earn about 50% more for their produce. They set consumers up as “digital farmers” who actively support and learn about farming activities to promote more conscious food consumption.
Their vision is to create a food economy in which those who produce food and those who consume it are connected. This moves consumers from passive cash cows for large corporations that prioritize profits over the well-being of farmers to actively supporting natural production and a more sustainable system.
Rifo Lab
Rifo Lab is a circular clothing brand with the vision of addressing the problem of overproduction in the clothing industry. Established in Prato, Italy, a traditional textile-producing area, the company produces clothes made from textile waste and biodegradable materials. There are no physical stores, and all orders must be placed online; everything is made to order, reducing excess production.
With an eye on social regeneration, all production takes place within 30 kilometers of their offices, allowing the business to support ethical and local production. They also work with companies that actively integrate migrants into the local community, sharing their local artisan crafts with future generations.
Ogyre
Ogyre is a digital platform that allows you to pay fishermen to fish for waste. When fishermen are out conducting their livelihood, they also collect a significant amount of waste from the ocean, especially plastic waste. Ogyre arranges for fishermen to get paid for collecting that waste, which in turn supports the local fishing communities, and then transforms the waste collected into new sustainable products.
Moving Towards a Regenerative Future
The masterclass concluded with a Q&A session, where it explained that working in regenerative businesses requires the same skills as any other business. But it also requires you to embrace a mindset where value comes from giving and that growth is about working together for a better future, and not just competition.

Riccardo Ocleppo’s vision for the Open Institute of Technology (OPIT) started when he realized that his own university-level training had not properly prepared him for the modern workplace. Technological innovation is moving quickly and changing the nature of work, while university curricula evolve slowly, in part due to systems in place designed to preserve the quality of courses.
Ocleppo was determined to create a higher learning institution that filled the gap between the two realities – delivering high-quality education while preparing professionals to work in dynamic environments that keep pace with technology. Thus, OPIT opened enrolments in 2023 with a curriculum that created a unique bridge between the present and the future.
This is the story of one student, Ania Jaca, whose time at OPIT gave her the skills to connect her knowledge of product design to full system deployment.
Meet Ania
Ania is an example of an active professional who was able to identify what was missing in her own skills that would be needed if she wanted to advance her career in the direction she desired.
Ania is a highly skilled professional who was working on product and industrial design at Deloitte. She has an MA in product design, speaks five languages, studied in China, and is an avid boxer. She had the intelligence and the temperament to succeed in her career, but felt that she lacked the skills to advance and move from determining how products look to how systems really work, scale, and evolve.
Ania taught herself skills such as Python, artificial intelligence (AI), and cloud infrastructure, but soon realized that she needed a more structured education to go deeper. Thus, the search for her next steps began, and her introduction to OPIT.
OPIT appealed to Ania because it offered a fully EU-accredited MSc that she could pursue at her own pace, thanks to remote delivery and flexible hours. But more than that, it filled exactly the knowledge gap she was looking to build upon, teaching her technical foundations, but always with a focus on applications in the real world. Part of the appeal was the faculty, which includes professionals who are leaders in their field and who deal with current professional challenges on a daily basis, which they can bring into the classroom.
Ania enrolled in OPIT’s MSc in Applied Data Science & AI.
MSc in Applied Data Science and AI
This is OPIT’s first master’s program, which also launched in 2023, and is now one of four on offer. The course is designed for graduates like Ania who want a career at the intersection of management and technology. It is attractive to professionals who are already working in this area but lack the technical training to step into certain roles. OPIT requires no computer science prerequisites, so it accepted Ania with her MA in product design.
It is an intensive program that starts with foundational application courses in business, data science, machine learning, artificial intelligence, and problem-solving. The program then moves towards applying data science and AI methodologies and tools to real-life business problems.
The course combines theoretical study with a capstone project that lets students apply what they learn in the real world, either at their existing company or through internship programs. Many of the projects developed by students go on to become fundamental to the businesses they work with.
Ania’s Path Forward
Ania is working on her capstone project with Neperia Group, an Italian-based IT systems development company that works mostly with financial, insurance, and industrial companies. They specialize in developing analysis tools for existing software to enhance insight, streamline management, minimize the impact of corrective and evolutionary interventions, and boost performance.
Ania is specifically working on tools for assessing vulnerabilities in codebases as an advanced cybersecurity tool.
Ania credits her studies at OPIT for helping her build solid foundations in data science, machine learning, and cloud workflows, giving her a thorough understanding of digital products from end to end. She feels this has prepared her for roles at the intersection between infrastructure, security, and deployment, which is exactly where she wants to be. OPIT is excited to see where Ania’s career takes her in the coming years.
Preparing for the Future of Work
Overall, studying at OPIT has helped Ania and others like her prepare for the future of work. According to the Visual Capitalist, the fastest-growing jobs between 2025 and 2030 will be in big data (up by 110%), Fintech engineers (up by 95%), AI and machine learning specialists (up by 85%), software application developers (up by 60%), and security management specialists (up by 55%).
However, while these industries are growing, entry-level opportunities are declining in areas such as software development and IT. This is because AI now performs many of the tasks associated with those roles. Instead, companies are looking for experienced professionals to take on roles that involve more strategic oversight and innovative problem-solving. But how do recent graduates leapfrog past experienced professionals when there is a lack of entry-level positions to make the transition?
This is another challenge that OPIT addresses in its course design. Students don’t just learn the theory, OPIT actively encourages them to focus on applications, allowing them to build experience while studying. The capstone project consolidates this, enabling students to demonstrate to future employers their expertise at deploying technology to solve problems.
OPIT also has a dynamic Career Services department that specifically works with students to prepare them for the types of roles they want. This focus on not only learning but building a career is one of the elements that makes OPIT stand out in preparing graduates for the workplace.
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