Udemy vs coursera data science

Udemy vs Coursera. Which is best?

What’s better Udemy or Coursera? the answer is: it depends on what you want. Lets see why we would choose Udemy vs Coursera and vice versa.

With so many online learning platforms out there, it can be hard to choose which one to trust and put our money on. The decision on the perfect platform for us has to consider our learning goal, time, amount of spare money that we want to invest in education, and overall likeliness of the experience.

In this post we will compare Udemy and Coursera, two very popular online learning platforms. However, the purpose is not to create a competition and pick a winner, as each of these platform suits a different kind of customer. Lets see why.

Udemy vs Coursera

udemy vs coursera data science

Lets start by seeing the background and goal of each of these platforms. Udemy is a global marketplace with more than 100.000 courses on many different topics: from marketing personal development or business to data science and machine learning. It offers a way for individual teachers to create content that they regard as relevant and post it there for pupils to enrol if they have the same opinion. Courses are offered on a wide range of prices, and there are a lot of discounts. Pretty much anyone can publish or receive a course from Udemy, with little effort, as the platform provides tools for the teachers or content creators to use.

Coursera on the other hand, is a more institutional platform. It was founded in 2011 by academics from the University of Stanford, created by top-notch researchers and educators to bring a massive offering of education to the internet population of the world through the use of Massive Online Open Courses (MOOCs). It offers free and payed courses, and certificates on a wide range of topics, despite having its origins on Computer Science. It has agreements and partnerships with top universities and organisations world wide, and their teaching is based on methods verified by top researchers.

As we can see, the platforms, despite both having the goal of teaching, have a different approach. Udemy is more oriented towards, fast, specific courses, that can be created by anyone, while Coursera is a more academic platform. This usually means that Udemy is cheaper than Coursera.

Udemy vs Coursera Learning approach

In Udemy, registration is free, and we usually pay one time for each course we want to take. These courses are built with video lectures, and most times assignments (programming assignments in Jupyter Notebooks most times in the case of Machine Learning courses) and maybe quizzies. While the quizzies have to be passed in order to be able to progress with the course, they are usually very simple, and not very challenging. They just test if you’ve been playing attention. The coding assignments also, are covered in video lectures most times, but are not actually graded: you don’t have to hand them in to pass the course. While this might sound good for the more lazy students, we would prefer if they were evaluated and graded.

Coursera, on the other hand, is a subscription service. You pay on a monthly basis and access as many courses as you want. If you are willing to invest time into your education, and put in hard work, this is probably the platform four you. If you want a more relaxed, self time approach, then Udemy is probably better. In Coursera, to pass the courses most time you not only have to pass the theoretical quizzies, but also to submit programming assignments, which from our point of view is a good way to fully check if the content of the course has been understood. However, we can get stucked in some programming assignments, and end up loosing a lot of time and getting frustrated.

To confront this, there are active blogs for most Coursera courses, where students and teachers can discuss and interact.

Udemy or Coursera for Machine Learning

The question of whether is Udemy or Coursera better, or if we should go to Udemy or Cousera for Machine Learning, has to be answered taking into consideration three things: interest in the topic, time we are willing to spend weekly/daily, and money that we want to spend.

If you are not sure whether you are very fond of a specific topic, and just want to know a little bit more about it, then you are better off taking an Udemy course: you will spend less money, probably less time, and you will better be able to evaluate if you like the topic or not. If you do, then you can carry on with Udemy courses or go on to take a Coursera one: for us Udemy is the perfect place to start, to discover, and to explore.

Once we know that we want to really learn about a topic, then Coursera takes the edge: its courses are really well built, have amazing support, and usually go more in depth than Udemy ones. Coursera is the place to go to adquiere and consolidate deep knowledge about topics of interest.

This marries directly with the topic that we will cover next: the certificate value of both platforms.

Udemy vs coursera certificate value

Both platform offer certificates for all completed courses, however, as we have discussed, because Coursera is backed up by many academic institutions, its certificate provide a lot more value than the ones from Udemy, which are just an online assurance that the course has been completed.

Coursera certificates have to be earned, through completing assignments that sometimes are quite challenging, while Udemy certificates are awarded sometimes without completion of any kind of test. Instructors of Cousera will look at the details of the work of the students before giving them any kind of certificate that fully accredits them as having successfully passed the specific course.

Coursera sometimes also offers the chance to take the courses for free, without earning a certificate, like we explained in the following post:

Our Personal experience with Udemy and Coursera for Machine Learning

We love both platforms and have used them, equally to learn. We started out by taking some of the Udemy courses listed on our Programming Courses Section from Udemy, like the ones by Jose Portilla. After, we have taken Machine Learning Courses from the same author in Udemy, to being learning about Machine Learning and artificial intelligence.

After completing these courses and having built projects, worked a little bit, and become fluent Data Scientist, we went on to deepen our knowledge taking Coursera courses like the Deep Learning Specialisation by Andrew Ng. Now, after having good experience and know how on how to build, and deploy Machine Learning applications, if we took a course to expand our knowledge, it would most definitely be on Coursera.

Conclusion

We have discussed when to choose Coursera vs Udemy and vice versa. They are both amazing platforms, and we deeply encourage anyone who wants to learn about Machine Learning and Data Science to take a look at their wide range of courses.

You can find the best courses from both platforms, to initiate your learning, or to go really deep into Machine Learning in our Machine Learning Courses section.

We hope you enjoy them, and that they serve you as well as they have served us!

Have fun, learn a lot, and enjoy Machine Learning!

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