Best machine learning courses in 2025

AI-powered technologies make their way into nearly all sectors, from driving assistants to health diagnostics or simple website chatbots. Growing employment opportunities increased the demand for machine learning specialists who can gain skills by enrolling in machine learning courses online.

Currently, finance, e-commerce, and healthcare industries actively seek ML developers, but there's ample opportunity in almost all business types. To help you get started, I have compiled a list of the best machine learning courses on Coursera. The Cybernews researchers fact-checked my findings and helped to select ML courses for starters and more experienced learners.

I aimed to strike a balance between introductory and more specialized machine learning classes. Below, you will find lessons you can complete in days and longer courses that can set you up on a machine learning career path. If you choose the latter, dedicating 10 weekly hours to studying is a frequent recommendation.

Top machine learning courses – shortlist

• Fundamentals of Machine Learning and Artificial Intelligence – best introductory course
• Machine Learning Specialization – ML application building for beginners
• IBM Machine Learning Professional Certificate – intermediate-level ML development
• Supervised Machine Learning: Regression and Classification – focused machine learning course
• IBM Introduction to Machine Learning Specialization – business-centric ML introduction
• Introduction to Machine Learning – focused on natural language processing

The best machine learning courses compared

Before we analyze each machine learning online course separately, let's see what each offers. Take a look at the table below for a side-by-side comparison.

Program name	Fee	Coursera rating	Number of courses	Duration	Difficulty level	Certificate	Best for
Fundamentals of Machine Learning and Artificial Intelligence	Free	4.4	1	1 hour	Beginner	No	Learning the basic concepts of machine learning and AI
Machine Learning Specialization	$49/month	4.9	3	2 months	Beginner	Yes	Developing real-world AI programs, deepening ML knowledge
IBM Machine Learning Professional Certificate	$39/month	4.6	6	3 months	Intermediate	Yes	Developing applicable ML skills, learning Jupyter Notebook and IBM Watson Studio tools
Supervised Machine Learning: Regression and Classification	$49/month	4.9	3	33 hours	Beginner	Yes	Developing ML models in Python programming language
IBM Introduction to Machine Learning Specialization	$39/month	4.7	4	2 months	Intermediate	Yes	Business-centric machine learning application development
Introduction to Machine Learning	$49/month	4.7	6	25 hours	Intermediate	Yes	Deepening machine learning knowledge, learning natural language processing

6 Best machine learning courses – our detailed list

Below is my detailed list of the best machine learning courses on Coursera. I recommend double-checking the difficulty level before enrolling, as advanced machine learning is a challenging discipline.

1. Fundamentals of Machine Learning and Artificial Intelligence – best for ML starters

Program name	Fundamentals of Machine Learning and Artificial Intelligence
Fee	Free
Number of courses	1
Duration	1 hour
Difficulty level	Beginner
Certificate	No
Best for	Learning the basic concepts of machine learning and AI

Learn more on Coursera

Amazon Web Services launched this fast-paced machine learning course for starters. It takes only 1 hour and explains the fundamental concepts of machine learning, deep learning neural networks, and generative AI.

Nearly 20,000 students have enrolled in this machine learning class, giving it an excellent 4.4 star rating. After completing the ML and AI theory, students are introduced to a variety of Amazon services that use this technology. In the end, they are redirected to chosen Amazon products to start developing practical skills.

In this 1 course, you will learn the fundamental concepts of ML and AI. I recommend starting with it to identify which AI branch interests you most and then picking more elaborate machine learning online courses afterward.

2. Machine Learning Specialization – courses from ML masterminds

Program name	Machine Learning Specialization
Fee	$49/month
Number of courses	3
Duration	2 months
Difficulty level	Beginner
Certificate	Yes
Best for	Developing real-world AI programs, deepening ML knowledge

Learn more on Coursera

This is one of the most popular machine learning courses on Coursera. It is taught by 4 instructors, including Andrew Ng, who is one of the most prolific names in the AI online courses field.

Over 600,000 students have enrolled in this 3-course series. The 4.9-star rating from over 32,000 reviews reflects its high quality. It starts with the introduction of the fundamental machine learning techniques but quickly switches to advanced ML algorithms, supervised and unsupervised learning, and how they are successfully used in Silicon Valley.

In this course you will work with Python coding language and its NumPy and scikit-learn libraries. It also introduces the popular deep learning framework TensorFlow. Simultaneously, instructors explain the best ML development practices to help prepare for the first career steps.

3. IBM Machine Learning Professional Certificate – course by IBM professionals

Program name	IBM Machine Learning Professional Certificate
Fee	$39/month
Number of courses	6
Duration	3 months
Difficulty level	Intermediate
Certificate	Yes
Best for	Developing applicable ML skills, learning Jupyter Notebook and IBM Watson Studio tools

Learn more on Coursera

This IBM course is for intermediate-level learners who already have experience in Python coding language, linear algebra, and statistics. The course takes up to 3 months and promises to prepare students for employment with a certificate from IBM.

The 6-course series has a great 4.6 rating with over 81,000 enrolls. IBM is one of the leaders in the artificial intelligence industry, and its instructors share personal experiences based on real-world examples.

To get the IBM certificate, you will work with Jupyter Notebooks and IBM Watson Studio tools. You will also use TensorFlow, Pandas, NumPy, and other libraries, so be prepared to do a lot of programming. This course focuses on supervised, unsupervised, and reinforcement learning topics.

4. Supervised Machine Learning: Regression and Classification – fast and informative ML course

Program name	Supervised Machine Learning: Regression and Classification
Fee	$49/month
Number of courses	3
Duration	33 hours
Difficulty level	Beginner
Certificate	Yes
Best for	Developing ML models in Python programming language

Learn more on Coursera

The Supervised Machine Learning course is a more focused part of previously reviewed Machine Learning Specialization so you will enroll for both automatically. However, this shorter segment takes only 33 hours if you require to deepen your supervised machine learning knowledge.

This course is also prepared by Andrew Ng alongside other DeepLearning.AI instructors. It has over 900,000 enrolls and a superb 4.9 rating from 27,000 reviews. A majority of reviews give it the maximum rating, outlining concise and information-rich lessons.

Although it is a beginner-friendly machine learning training, you should have basic programming and high-school mathematics levels. You will learn to build ML models in Python language and its NumPy and scikit-learn libraries. You will also get a certificate, which is beneficial when securing employment opportunities.

5. IBM Introduction to Machine Learning Specialization – ML and data analytics courses

Program name	IBM Introduction to Machine Learning Specialization
Fee	$39/month
Number of courses	4
Duration	2 months
Difficulty level	Intermediate
Certificate	Yes
Best for	Business-centric machine learning application development

Learn more on Coursera

Similar to Supervised Machine Learning, this is IBM's narrowed-down introduction to machine learning. It can also be used to complete the IBM ML Professional Certificate last two courses.

In comparison, it lasts 2 months and focuses on supervised and unsupervised machine learning, as well as a course on data analysis. Alongside lessons in Python development, you will also learn Structured Query Language (SQL), which is widely used to retrieve data and manage databases.

Over 700 reviews give this machine learning course a high 4.7 rating with over 18,000 participants. Keep in mind that this is an intermediate level, so you must have at least a basic understanding of statistics, linear algebra, Python programming, and data analysis. Upon completion, you will get an IBM badge and a Coursera certificate.

6. Introduction to Machine Learning – course from top-ranking university lecturers

Program name	Introduction to Machine Learning
Fee	$49/month
Number of courses	6
Duration	25 hours
Difficulty level	Intermediate
Certificate	Yes
Best for	Deepening machine learning knowledge, learning natural language processing

Learn more on Coursera

Instructors from the top-ranking US Duke University offer this 25-hour introduction to machine learning. Participants rate it at 4.7 stars, outlining elaborate explanations of ML basics by professional lecturers. However, a bit less positive reviews reveal a lack of practical assignments and a focus on deep learning.

The course consists of 6 modules. After learning the basic concepts, you will switch to neural networks and natural language processing afterward. The course completes with an introduction to reinforcement learning.

Although this online machine learning course is set for the intermediate level, it introduces the discipline with as little mathematics as it can. I strongly recommend this course for students deeply interested in natural language processing, as it explains how ML systems recognize text.

How did we select the best machine learning courses?

Machine learning is a broad discipline that is used in increasingly more industries. This also means that there are ample machine learning programs to kickstart your career. Here's what I considered to narrow the list down to the six best.

• Industry relevance. I look for up-to-date content that offers real-world application examples and the best machine learning implementation practices.
• Certification. Five out of six courses offer Coursera certification that strengthens your competitive position. Simultaneously, IBM's professional certification course also provides IBM's badge on completion.
• Expert instructors. You will find courses created by well-known AI expert Andrew Ng. Simultaneously, you can learn from IBM professionals and lecturers from top-ranking Duke University.
• Flexibility and accessibility. All courses allow moving at your own pace. I also included courses for beginners and more experienced learners and verified that certifiable courses offer multi-language support.
• Student feedback. Participant ratings and first-hand reviews were critical to forming a review based on personal experience.

What is machine learning, and why is it important?

Machine learning is a discipline in the broader artificial intelligence field. As the name suggests, this particular subfield teaches how machines can learn autonomously without direct human supervision. In other words, machines are taught to come up with reliable solutions to problems without direct human instructions.

This technology has revolutionized numerous internet technologies. For example, ChatGPT and Google's Gemini generative AI chatbots utilize machine learning. Machine learning applications also automate numerous tedious tasks like recognizing scam patterns for fraud detection or optimizing customer support with AI-powered chatbots.

ML is also widely used for e-commerce platform personalization to identify user behavior patterns and suggest commodities accordingly. It also applies to streaming content and similar personalizations. ML applications can handle massive and complex datasets, eliminating human error and making this technology highly valuable in today's data-driven environment.

What are the benefits of machine learning courses?

In 2025, software development is among the most stable and best paid positions. Within the IT industry, machine learning employment opportunities steadily grow each year, which is likely a lasting trend. Here are the major benefits of machine learning courses.

• Career advancement. Coursera machine learning courses open up possibilities to become a machine learning engineer, data scientist, artificial intelligence specialist, and more.
• In-demand skill set. Healthcare, finance, technology, and numerous other sectors are actively looking for future employees with machine learning development skills.
• High salary potential. As you will see from the following section, these specialists secure competitive salaries, reaching up to $200,000 in senior positions.
• Problem-solving framework. In your work, you will learn to solve complex data-driven problems, which is a rewarding challenge in itself.
• Portfolio building. The software development market is competitive. If you have an online machine learning course certificate, you significantly increase the chances of being noticed by businesses.

How much does a machine learning specialist earn on average?

Machine learning specialist salary depends on work and experience level, but also geographical location and business policies. With the help of the Cybernews research, I have overviewed the salaries on popular employment websites. Here's an estimate of what you can expect in the US.

Entry level	$85,000 - $110,000/year
Mid-level	$110,000 - 140,000/year
Senior level/lead position	$150,000 - $200,000, often with equity and bonuses
Freelance/consulting	$50-$150 hourly rate

Keep in mind that this is a rough quote, as employment opportunities significantly depend on local businesses. However, personal experience, knowledge, and skill set are the most significant factors, so the machine learning courses you take online will pay off with time and effort.

How to choose the best machine learning course for your needs?

Coursera machine learning courses are not for the faint of heart, so consider the following aspects before you subscribe to a months-long learning journey.

• Skill level. Are you a beginner, intermediate, or advanced student? Choose a course accordingly, as advanced levels may be overwhelming without the required knowledge.
• Programming requirement. Python coding language is primary in most machine learning courses. However, you may also find C++, R, and Java, so inspect which one you know best and pick accordingly.
• Learning format. Double-check whether the courses offer video lectures, interactive coding labs, as well as mentorship, or peer forums.
• Project work. Courses that offer an opportunity to work on a real-life project provide invaluable experience and preparation for employment.
• Certification. ML courses that offer certificates or bonuses, like the IBM badge, will help you stand out from the competition.
• Course duration and flexibility. Answer yourself how many months and weekly hours you can dedicate to ML courses.
• Price vs. value. Evaluate whether your gained knowledge will help pay for the courses in the future.

Final word on best machine learning courses

Machine learning courses are an exciting, challenging, and rewarding journey if you put your mind and dedication to it. For beginners, I suggest starting at the free AWS Fundamentals of Machine Learning and Artificial Intelligence course. However, after a quick hour, you should decide on a more elaborate and specialized path.

The Machine Learning Specialization, instructed by AI expert Andrew Ng, comprehensively conveys the complexities of ML. Meanwhile, IBM courses for intermediates offer instructors from one of the biggest IT brands and a neat IBM badge to secure lucrative career positions. In the end, it's up to you to decide where to start and how to proceed with your chosen learning path.

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