Did you know that your favorite Netflix recommendations are brought to you by implementing machine learning?
If you’re following the news in the programming and artificial intelligence worlds, machine learning is probably not a foreign concept to you. The future seems bright for machine learning, as there are just too many things that computers can do instead of humans. No wonder so many people are looking for Coursera machine learning courses.
This time-saving concept seems to be the future of technology. So, if you’re among the people who want to keep up with the times changing, you might want to think about learning machine learning. One of the platforms to do it on is Coursera.
Coursera is one of the leaders of the online learning community. The well-established online learning platform provides great courses for various topics, including Coursera machine learning. Therefore, you shouldn’t miss out on this rapidly emerging technology and also choose to learn it on a reputable learning platform.
So if you're interested in machine learning, you must want to find out what the best courses are. Find them below!
Table of Contents
- 1. What Is Machine Learning?
- 2. Coursera Machine Learning Courses
- 2.1. Stanford Machine Learning Course (Enroll Here)
- 2.2. University of Washington - Machine Learning Specialization (Enroll Here)
- 2.3. Machine Learning for All Course (Enroll Here)
- 2.4. Advanced Machine Learning Specialization (Enroll Here)
- 2.5. Machine Learning with Python Course (Enroll Here)
- 3. Conclusions
What Is Machine Learning?
Before we get to the part where I recommend you the best Coursera machine learning courses for you to take, we must first have a brief introduction to what machine learning is. Machine learning, by definition, is the process of teaching a computer system to make accurate predictions when fed data.
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The difference between software and machine learning is that software relies on a human-written code, while in machine learning, the machine learns by itself. In a way, machine learning is closely related to artificial intelligence.
However, this simple definition doesn’t do machine learning any justice. Machine learning is a really complex topic that takes a while to grasp fully. However, it can be done by taking Coursera machine learning courses!
So, if you’re interested in expanding your horizons and learning more about this up-and-coming topic, I’d definitely advise checking out some of the best Coursera machine learning courses available.
While it might be hard to choose a reputable course, especially when choosing blindly, there are ways to avoid that. I’m here to save the day, as below, I’ll provide the best Coursera machine learning courses.
Coursera Machine Learning Courses
Now, let’s get to the part that you came here for—the best Coursera machine learning courses. You should keep in mind that every person is an individual. Therefore what suits one might not suit another. That’s why here I’ll present a few alternatives for you to choose from.
So, let’s see, arguably, the best Coursera machine learning courses!
Stanford Machine Learning Course (Enroll Here)
- Platform: Coursera
- Offered by: Stanford
- Duration: 60 hours to complete
- Price: Free
- Certificate: Yes (paid)
- Level: Beginner
- Where to apply? Here
Stanford Machine Learning course is something that’s searched for a lot. Another extremely popular search is Andrew Ng Machine Learning course. I bet you’ve already heard people mentioning these two course names.
It’s important to note that the Coursera Stanford Machine Learning course is also known as Andrew Ng machine learning course, so don’t make the mistake of thinking these two are separate courses.
The course is among the top-rated Coursera machine learning courses. While the Andrew Ng machine learning course being created by Stanford might intimidate some people, I’d strongly advise you not to worry about it. The Stanford Machine Learning course is aimed at beginners who want to get a broad understanding of machine learning.
While you would definitely benefit from having been acquainted with the technical vocabulary or at least knowing some theory about programming so you could compare machine learning with programmed software, it’s not a necessity.
Learning from Andrew Ng machine learning course, you will be taught from the very basics to the smaller intricacies of machine learning. So, if you’ve been thinking of applying for a machine learning course, give Stanford Machine Learning a chance!
Still wondering why you should? Well, let’s compare the attendance of the most popular Coursera machine learning courses. As of now, Andrew Ng machine learning course has 3.8 million students. The second most popular one on Coursera has comparatively little: 390 thousand attendants.
Judging by the number of people choosing the course, and also by the fact that the general satisfaction with the Coursera Stanford Machine Learning course is high, I definitely recommend this particular course.
University of Washington - Machine Learning Specialization (Enroll Here)
- Platform: Coursera
- Offered by: University of Washington
- Duration: Approximately 7 months to complete
- Price: Free
- Certificate: Yes (paid)
- Level: Intermediate
- Where to apply? Here
Let’s say you’re opposed to the Stanford course, maybe you’re not a huge fan of Andrew Ng, or maybe you believe that that course is way too short for you to achieve the level in machine learning that you’d like to reach. There are alternatives.
One of the best would be the Machine Learning specialization. Wondering why it is good? Well, first of all, it’s a specialization. That means that it’s not a simple course but a long-lasting study program that will cater to a larger portion of your machine learning needs.
The specialization takes approximately 7 months to complete. What can you learn in 7 months? Well, a lot, compared to the previous course that takes around 60 hours to complete. This specialization is much more suitable for those who are serious about machine learning.
While the aforementioned course might be more suitable for those who are looking to learn about machine learning as a hobby, this one will likely prepare you for machine learning more professionally.
The subject is rather broad, and you might need hands-on experience to put the theory into practice. However, there’s a lot of information covered and made simple for you. Therefore the extra effort you’d need to put in it would be minimized.
However, if you’re only interested in grasping the bare minimum of the course, maybe you’re doing it just for your own interest and are not looking to implement the knowledge, you might be better off sticking to another course. You should keep your motivation and goals in mind before choosing a course.
Still not convinced? Neither of these two Coursera machine learning courses interest you? Fortunately, I have some more options for you to explore.
Machine Learning for All Course (Enroll Here)
- Platform: Coursera
- Offered by: University of London
- Duration: Approximately 22 hours to complete
- Price: Free
- Certificate: Yes (paid)
- Level: Beginner
- Where to apply? Here
Another great Coursera machine learning course. This course is aimed at beginners who have no idea what machine learning is. What I have to note about the course at the very beginning of talking about it is that it takes around 22 hours to complete.
You might not see anything bad about it. You might be right. If what you’re interested in is being able to participate in conversations on a more shallow level about machine learning, this course has you covered.
However, if you’re interested in learning more deeply about the topic and if you have hopes for implementing it later in the job sphere, you might want to reconsider this course.
You don’t have to drop it fully. I believe that the more courses you take, the better your knowledge will be. You could use this course to test whether your interest in this topic is real and isn’t going to fade the moment things start getting difficult. Also, you could use it as a brief introduction as a base for further studies.
So, a good option would be starting with this course, and if you find yourself eager to learn more, you should consider taking more extensive courses such as the previously mentioned Machine Learning Specialization.
Advanced Machine Learning Specialization (Enroll Here)
- Platform: Coursera
- Offered by: Higher School of Economics
- Duration: Approximately 10 months to complete
- Price: Free
- Certificate: Yes (paid)
- Level: Advanced
- Where to apply? Here
This specialization might appear a little confusing by the way they present themselves. At first, you notice the “advanced” in the name and automatically assume that this specialization is not for beginners.
However, having read the description of the course, you’ll see that they claim to provide the introduction to machine learning, only then moving on to advanced topics.
If I were them, I’d change the formatting, but let’s try to make some conclusions about the course disregarding the issue of inconsistency. The course claims to provide extremely extensive knowledge about machine learning, deep learning, reinforcement learning, natural language understanding, computer vision, and Bayesian methods.
Keep in mind that they have time to provide all the knowledge, as the specialization lasts for approximately 10 months, making it the longest-lasting course on this list. Therefore, you can get to see all the intricacies of machine learning.
Also, it’s important to note that they claim to provide lots of hands-on experience. Taking this course, you’ll get to apply what you have learned, taking the knowledge, and understanding to the higher levels. That’s a really good thing to find in a course.
However, once again, I’d advise you to first check your motivation levels. The course lasts for 10 months, and while no one’s going to forcefully make you stick to it, the better alternative would be taking a shorter course which you’re going to finish.
Ask yourself what you’re going to use the knowledge you get for. If you’re seriously interested in the course and would like to apply it in the job field, or you see it as an extremely passionate hobby of yours, don’t hesitate and take it.
However, if you’re simply curious about the topic without knowing anything about it yet, you should first test the waters with the shorter courses such as Stanford Machine Learning or Machine Learning for All.
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Machine Learning with Python Course (Enroll Here)
- Platform: Coursera
- Offered by: IBM
- Duration: Approximately 22 hours to complete
- Price: Free
- Certificate: Yes (paid)
- Level: Intermediate
- Where to apply? Here
The last course I’d like to introduce is Machine Learning with Python. As the name suggests, you need to keep in mind that you’ll need to be knowledgeable in Python programming language if you’re looking to take this course.
The course takes approximately 22 hours to complete. That’s not a lot. However, since it’s aimed at those who already have some specializations in the programming field, it might be justifiable. By taking this course, you’ll be able to understand the relation between Python and machine learning.
Also, the course claims to concentrate on topics such as machine learning applied to the real world, providing info about supervised VS unsupervised machine learning, model evaluation, and machine learning algorithms.
Having finished this course, you’ll get the ability to add some skills to your resume as well as some projects completed to your portfolio.
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However, if you’re a beginner looking for courses that would prepare you for working in the field, this course might not be it. Can it provide interesting insights about machine learning? Absolutely! Will the 22 hours be enough to achieve an advanced, or even intermediate, level in machine learning? Most likely not.
However, this course is on the list because it has some interesting sections other courses don’t emphasize. There have been mentions of learning about how machine learning can be applied to the real world. Also, you’ll get to practice with real-world machine learning examples, which is an invaluable experience.
Therefore, if you’re looking for a shorter course on machine learning and would also like to have a course that isn’t only plain theory but is filled with real-world examples, give this course a try!
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Conclusions
Coursera machine learning has a great reputation in the field of online learning platforms' courses. You can find some of the best specializations and courses here on Coursera. There are plenty of different Coursera machine learning courses, but here we tried to provide the most popular, top-rated, and interesting ones.
The first course that’s majorly popular in the industry is the Coursera Stanford Machine Learning course, also known as Andrew Ng Machine Learning course. Others you should check out are Machine Learning Specialization, Machine Learning for All, Advanced Machine Learning Specialization, and lastly, Machine Learning with Python.
All these Coursera machine learning courses could provide you with great insights; however, you might want to choose one or even combine a few from the list. I’d suggest taking your motivation and where you want to apply your knowledge into consideration and decide whether you’ll take a long-lasting specialization or you’ll stick to a simple course.
Having done that, make sure to read well about the differences in the courses, and try to make a choice. Don’t be afraid that you’ll have to choose and stick to one course. You can explore them all and even more courses than presented in the list!
So, now that you know all about the Coursera Machine Learning courses, it’s time to take action. If you would like to learn more about what machine learning is, feel free to check out our guide on it. Having done that, don’t hesitate to go to Coursera and choose the course you’d like to take to learn more.
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