Is Datacamp Good for Machine Learning?

Datacamp is an online education platform that specializes in video courses related to data science. It offers over 300 courses, including machine learning with Python and R, but how good are Datacamp’s machine learning courses? Are they worth paying $25 a month?

Datacamp is good for machine learning, particularly for beginners. Its organized career track will help you learn the skills required for machine learning from scratch. However, the videos sometimes lack depth, so you may have to complement them with books or other courses.

In this article, we’ll discuss everything you need to know about learning machine learning on Datacamp. We’ll discuss the course structure and other considerations to help you decide if you should subscribe to Datacamp.

Click Here to Sign Up for DataCamp Today!

Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!

Datacamp Machine Learning Career Track

The best thing about Datacamp is that it has several learning paths for different professions, such as data science, data analysis, data engineering, and machine learning. These career tracks are meant to provide you everything you need to know to become proficient. No prior knowledge is required to start learning.

Before starting the machine learning career track, you’ll need to learn Python or R . Datacamp’s video courses are ideal for beginners. You perform hundreds of exercises and solve problems to solidify your learnings. Once you’re proficient in any of these languages, you can move on to the machine learning path using that language.

Note that Python is usually the recommended language for machine learning. R is typically used in projects where data visualization and statistics are the chief requirements. Here are the links to Python programming and R programming on Datacamp.

The machine learning course with Python covers supervised, unsupervised, and deep learning. It has 23 separate classes and is 93 hours long. On the other hand, the R machine learning course doesn’t teach deep learning. It is a collection of 15 courses and is 61 hours long.

The classes teach you things like how to process data for modeling, train machine learning models, and adjust parameters for optimal performance. You’re also introduced to popular Python libraries like scikit-learn, SciPy, and TensorFlow. If you’re learning with R, you’re introduced to caret, sparklyr, and rstanarm.

All in all, DataCamp offers an amazing value to most learners. It is one of those programs that you just cannot go wrong with it.

Click Here to Sign Up For DataCamp Today!

Unique Features of Datacamp

Datacamp offers hundreds of courses for a single subscription fee. Along with the machine learning video course, you also get access to practice challenges, a few projects, and the skill assessment tool (more on that in a moment). If you want to get a feel for how machine learning is taught in Datacamp, you can create a free account and access the first chapter of every course for free.

Datacamp provides you video and text-based instructions using the in-browser coding environment. There’s no need to install any software to start learning. You can code in Python, R, SQL, and other programming languages from the comfort of your browser. This is one reason that makes Datacamp excellent for absolute beginners.

Another unique feature is Datacamp Signal. It is a skill assessment tool that measures your level of expertise in a skill. Knowing what topics to learn is a problem that all self-learners face at some point in their journey. Datacamp’s skill assessment tool is designed to test your strengths and identify your weaknesses to know what skill gaps are holding you back. This tool is also available as part of free membership.

So, as you can seen, DataCamp is packed full of great features that would appeal to most beginners in machine learning (or data science in general). So, don’t wait!

Sign Up for DataCamp Today!

What Are the Downsides of Datacamp?

As we’ve discussed, Datacamp holds your hand and walks you through the fundamentals and advanced programming and machine learning concepts. This may be convenient in the beginning, but you’ll soon feel like you’re not really doing much.

For example, the exercises are essentially fill-in-the-blanks where most of the code has already been written. Although this gradually changes as the course progresses, it would’ve still been better to let you do most of the stuff.

You may also notice that the content is often rushed, i.e., it lacks the kind of depth you would expect from a career track. Think of Datacamp courses as crash courses. They’re excellent as a refresher and for getting a high-level overview of the subject. Most assignments are non-challenging and easy. Although some real-world datasets are used, the exercises are often impractical due to their fill-in-the-blanks approach. 

But, even you are a data science or machine learning enthusiast at an advanced learning stage, the real world projects that DataCamp offers makes it totally worth it for you too.

Click Here To Get Started With DataCamp Today!

Who Should Use Datacamp for Machine Learning?

Overall, Datacamp is a great platform, and you can use it to learn many tech skills. However, it’s not meant for everyone. Datacamp should be used by newcomers who want to get a taste of what machine learning and data science feel like. Their courses will help you become comfortable with programming.

However, if you’re a do-it-yourself type of person, you may not appreciate Datacamp’s hand-holding. As you move toward more advanced concepts, you’ll need to look for other books, courses, or tutorials covering ML concepts in more detail than Datacamp.

Is Datacamp a good platform for learning machine learning? Yes. Should it be your only resource? Not at all.

But, if you consider yourself a beginner: DataCamp is the course I would most recommend.

Click Here To Get Started With DataCamp Today!

What Are the Alternatives to Datacamp?

As we’ve discussed, Datacamp is great for learning the fundamentals of machine learning and introducing yourself to various ML concepts. But what if you want to dig deeper?

The first thing you can do to dig deeper is to read books by industry experts. Python Machine Learning by Sebastian Raschka is a top-rated guide for people already familiar with Python. I highly recommend reading my article on the 15 best books for machine learning with Python for more book suggestions.

But are there any video courses that teach machine learning in-depth? Fortunately, various university courses take the academic approach to machine learning. Here are some alternative sites that offer comprehensive machine learning courses:


EdX and Coursera provide more depth than Datacamp when it comes to machine learning. Their courses follow the academic approach, meaning their content is similar to what you would get if you took the same course from a university.

EdX has lots of in-depth courses on machine learning. You can watch them for free, with access to all course materials and assignment exercises. However, you’ll have to pay to obtain a verified certificate.

For example, Columbia University’s machine learning course offers a comprehensive overview of machine learning. It helps you master the fundamentals of machine learning algorithms.


Like EdX, you can access Coursera classes for free, but you won’t get a completion certificate. Stanford’s Machine Learning course taught by Andrew Ng is a top-rated class on this subject. It covers a lot of ML theory, helping you understand the behind-the-scenes of ML algorithms. It has become a staple course in machine learning, and you cannot go wrong with it.

The only caveat is that this course uses Octave/MATLAB instead of Python. But don’t worry, I’ve written a full article on Octave’s significance in machine learning and how you can learn from Andrew Ng’s course using Python. Read the post here: Is Octave Good For Machine Learning?

Additionally, if you are looking for DataCamp alternatives and are a beginner, the one course on Coursera that I would truly recommend is the IBM Data Science Professional Certificate. It has great industry recognition and successfully transforms one into a data science ninja. Read my article: Is IBM Data Science Professional Certificate Worth It? for an in-depth review of this course.

Or, Click Here to Sign Up For This Course Today!

(Coursera gives you a 7-day free trial, so it is completely a risk free sign up for you!)


Datacamp is a popular online education platform focusing on topics related to data science. It also offers machine learning courses with Python and R programming languages. 

Datacamp courses are suitable for introducing yourself to machine learning. You will see a huge difference in your programming skills after practicing for a month on Datacamp.

However, students report that these classes don’t offer a lot of depth. So you’ll likely need to enroll in other courses that dig deeper into machine learning concepts. EdX and Coursera have such university ML courses, and you can watch them for free.

But, for most people: DataCamp is the program to go with!

So, don’t wait! Click Here To Sign Up For DataCamp Today!

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

  1. Machine Learning Scientist with Python. (n.d.). DataCamp.
  2. Machine Learning Scientist with R. (n.d.). DataCamp.
  3. My review: Unimpressed with Datacamp (for Python). (n.d.). reddit.
  4. Tayo, B. O. (2019, February 22). Data science and machine learning for beginners: DataCamp versus the academic approach. Medium.

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Daisy is the founder of Passionate for the field of Data Science, she shares her learnings and experiences in this domain, with the hope to help other Data Science enthusiasts in their path down this incredible discipline.

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