This review is updated based on DataCamp 2021 (for those wondering if the website has changed).

My story with DataCamp started in the 2020 lockdown. We have received from our university a confirmation of joining a Datathon and at the same time, a free 6 months subscription.

My goal was to become a Data Scientist or Analyst, however, I was not sure how to do it.

An arabic proverb says, "if it's free, benefit from it". So I did exactly that. I started my "Data Scientist Track with Python", doubting whether it might be a highly valuable certificate to obtain.

The amount of hours required to finish the full track did not motivate me at the beginning, however, I kept pushing. Day after day, hour after hour.

I stayed on track with a minimal goal of one chapter per day on my bad days and one course or more per day on my good days. It was not easy, I cannot hide that. Some days, it would take me 2 hours to finish one chapter (procrastination) and some other days, I used to rage quit because of not being able to find the solution. However, as James Clear says in his book "The Atomic Habit", 1% of progress per day is better than 0. Because, compounding growth.

Fast forward a year from those days, I am a proud Data Analyst. I did two internships at Big4 companies (due to the skillset I acquired from DataCamp). So was it worth it? Hell yeah it was!

I have updated my initial blog on whether DataCamp is worth it or not.

I tried to answer as many frequently asked questions in a concise way. All my answers are based on my own reflection and research (the facts will be easy to identify, my opinions are also easy to identify).

The reader should keep in mind that DataCamp will not get you the job you want; it is an upskilling tool. Does it serve its purpose? Yes, it does. Is it an ultimate/free-pass tool to get a job? Absolutely not.

Please if you have any more questions you would like to be answered let me know. I wouldn't mind answering you directly on this post (and get inspiration to update the blog).

In summary:

I am a master of AI student who had 0 to basic coding experience in Python (Bachelors of Civil Engineering). I started learning on DataCamp the career track titled "Data Scientist Track With Python". It gave me a huge boost to start my career in data analysis and data science.

The next courses I am planning to take are in Data Engineering (It would boost my experience for the job).

DataCamp is known for its interactive learning style with bite-sized lessons in Python, R, SQL, and machine learning. The platform is beginner-friendly and easy to navigate. You can complete exercises in-browser without needing to set up any tools.

The good part is how smooth the experience feels. Concepts are broken down step by step and there’s instant feedback on your code. For someone new to data science, it builds confidence quickly. Their career tracks give a structured path to follow.

But here’s the issue. Many users feel the learning is too guided and lacks depth. You write small bits of code but don’t learn how to solve open-ended problems. There’s limited focus on real project-building, and no exposure to working with messy data.

Job readiness is another concern. While it helps with basics, the course alone won’t prepare you for technical interviews or practical roles. You’ll need to go beyond their exercises and build full-scale projects on your own.

So overall, DataCamp gives a smooth intro to data science but stops short of making you truly job-ready. Half of its value depends on how much more you’re willing to do after finishing the track.

So, been learning some DE concepts (DW, Data Lakes, etc) But i really struggle with coding, and did some DataCamp free material, i really liked It Have any of you used the Premium version? Is It worth It?

I am about to complete my B.COMM in Finance & Analytics and would like to go the analytics route and work towards becoming a data scientist. Will Datacamp be useful for me in pursuing that career path? I have knowledge in C and Python already to work with.

Which do you think is best for learning data science in python?

Hey everyone! I'm about to graduate with a degree in statistics and want to specialize in machine learning/AI. I'm considering subscribing to Datacamp Premium so I can specialize for future job openings here in Brazil, improving my CV/resume.

Is this a good idea? As I mentioned, I already have a foundation in statistics thanks to my undergraduate degree; I'm even working on my final project related to the topic!

Good morning, everyone!

A few days ago, I came here asking for recommendations on courses to learn programming, focusing on Data Analysis/Science. I did a lot of research and ended up finding DataCamp. I watched the free introductory module on SQL and Python (both geared towards data analysis) and liked it. I took advantage of the 50% off the annual plan promotion and subscribed.

About the subscription:

I paid in full with my credit card (Itaú), but I managed to pay it in installments through the bank's app. In total, it was R$485.00 + R$485.00 + R$17.00 in conversion fees, totaling R$680.00 in 10 installments. I did some calculations later, and it seems like the fee would be lower with Nubank using the installment option via Pix.

For those who are in doubt (and like me, are beginners in programming):

I highly recommend DataCamp. They start from the basics and, daily, suggest which chapters to review through exercises. Plus, you can practice as many times as you want, anytime.

Suggestions (if you want them):

• The videos are short but very straightforward. I recommend using DeepSeek or ChatGPT to follow the lessons and clarify doubts.

• Each module has about 4 videos, followed by exercises. But I suggest supplementing with other sources, such as real-world cases or extra exercises (you can easily find them on GitHub).

• In parallel with DataCamp, I'm doing the Google Data Analyst track (Coursera). I got financial aid from the platform and only paid US$2.90 per course. Coursera is more theoretical, while DataCamp is more technical and practical—that's why the combination of the two has been great.

• On Coursera, you'll find many other courses in various fields and you can request financial aid for most of them (a golden tip I found on YouTube).

DataCamp's advantages:

• Organized and well-planned structure.

• You can take exams for professional certifications (such as Data Analyst or Data Scientist).

• Each track has several courses, and each completed course generates a certificate, which gives a sense of progress and motivation to continue.

Anyway, I hope this helps those who are in doubt, just like I was. If you want to invest in a Data career, it's worth it! I plan to try the Dev tracks as soon as I finish the roadmap I created.

https://youtube.com/watch?v=Q4dpNKJJl7A

Thoughts on this?

I don't know what subreddit is best for this post. Sorry if it's not this one.

So I'm a data analyst, not a data scientist. I just finished grad school (not data science) and I'm between jobs and about to move to a new city, so I've been taking the last few weeks to go through Datacamp's material fairly intensely (~4 hours a day) to upgrade my skills before I get my hopes and dreams crushed by the job market.

...

The first thing I noticed about Datacamp was that they did a lot of stuff for me. I'd open up an exercise and most of the code had been written already, with a couple of spaces with '____' where I should fill in the right answer. I thought this was really frustrating, because there was never any point in the process where they explained to me why we needed to perform whatever operation it was. I'm like 50 hours in, and I'm not sure I could do any of this without Datacamp's prompting. I think this is the worst part of the Datacamp curriculum. I feel that I'm paying Datacamp to teach me Python syntax and when to use it (not just how to use it), and I feel like I'm not learning either of those things.

Second, although Datacamp courses offer short video segments that putatively "teach" the course, the exercises were essentially big text boxes. Oftentimes the video and text would be somewhat out of sync, and sometimes it felt like entire sections had been omitted between text and video. This made watching the videos almost completely optional, and considering most of them are shorter than 5 min, there was never enough time to substantively introduce the material anyway.

Third, the exercises rarely feel practical. There are some nice real-world datasets used, but because of what I describe in my first paragraph, it's hard to actually interface with them. You're not really working with them yourself. Beyond that, it doesn't feel like Datacamp spends a lot of time trying to motivate the problem. Why do we need to take this approach, etc. There are often domain-specific considerations that influence how the problem may best be solved, and that stuff is completely omitted. This ends up meaning that these supposedly practical exercises end up anything but.

I had a really long paragraph here about how I dislike their two-part statistics course. TL;DR: I thought the treatment of linear regression was really shallow and incomplete (there's no mention of residuals at all, for example), and I thought leaving out multiple and logistic regression meant it didn't provide enough for students to actually learn how to work with data. I've never worked as a data scientist, but I understand that those two are important. They're already super useful as an analyst.

That's not to say that Datacamp is terrible. I really liked some of the data viz stuff they've got (Seaborn and Bokeh are awesome), and I think their first couple of intro to Python courses are helpful. I've heard great things about their R courses, as well. And Datacamp has got a great platform for what they're doing.

I'm certainly going to finish my month of Datacamp, but I don't think I'll be resubscribing. I know it's kind of a cheap shot, but I feel like I might subscribe to one of their competitor products in the hope that they can teach me more of the syntax and thought process behind this stuff. I'm disappointed to be paying somebody to teach me, only to have to Google what they're supposed to be teaching.

So I am new into programming, I have been using Datacamp recently to learn some Python, but I have finished my first chapter so now if I want to continue then I need to pay them 40 euros a month. Now I want to ask if there are any other cheaper, or even free, courses that I should follow or if Datacamp is the best one and I should pay the subscription.

Hey, guys. I am a full stack developer looking to upskill myself in AI and ML. I have heard of and read about DataCamp before. Currently, its premium subscription is on sale, so I am considering buying it to learn and earn certificates.

Those of you who have used it before, can you share your thoughts on the quality of its courses or suggestions for any better alternatives?

Thanks in advance!

"Has anyone landed a job, or at least been getting interviews, from using DataCamp? If so, which topics did you study and which certifications did you earn, for data analysis?"

It took me 2 years to get this certification, yes I was slow as I had a lot of other stuff too.
A few months ago I put a post here, which also became one of the top posts of this group.

After around a week or two, I realised:
The current market was way beyond (above) my skills. I basically knew nothing. Well technically its not wrong....From their track I studied basically most of everything that falls within the definition and job description of Data Science.... Its basically the market that has converted most of Data Science into Machine & Deep Learning

Advice:
For Data Analysists:
A lot of people have been hitting me up since that post and asking me is Data Analyst worth... Well tbh I can't tell that. You mightv'e to ask someone who's already done that track. From what I know, yes today if I wanna step in that, I can very easily do it after my track of DS. But I dont have knowledge of market in DA.

For Data Scientists:
DONT DO THE DATA SCIENTIST CAREER TRACK.
Yes you could pick a few important things from it like Intro, EDA, SQL etc. But just try to wind it up ASAP. The only good thing in Datacamp is, it provides good practical experience, practice.
If u really want to do it from Datacamp, go for the "MACHINE LEARNING SCIENTIST" career track. It might train you well enough.

Summary:
I wasted 2 years for a certification that just gave me basic foundation of something I wanted to make my complete career in.

• Look for some other platform.

• If DataCamp, then "Machine Learning Scientist in Python" >>> "Data Scientist with Python"

Hello all programmers,

I am a cs student who is currently very interested in focusing on data science or data engineering and I came to ask for advice from people who are currently working on how I can continue learning. I was looking around and I saw that data camp is a good option, what do you think.

Edit: Do you know of any other better teaching platform?

Btw sorry if my english is bad I am not from an english speaking country :p

Started the MSDA program June 1 and so far, so good except I find myself getting gradually more and more frustrated with DataCamp. I have decades of programming experience in multiple languages (including Python) as well as data analysis, reporting and database admin experience so I feel like this should be relatively straitforward for me, but I’m stumbling with some of the course work. A lot of the DataCamp instruction feels inconsistent and poorly designed. Am I alone in that? Trying to gauge whether it’s me or the material.

I'm a relatively new R user. Up to now, I thought I was pretty good. Noticing a lot of people posting smaller and more efficient chunks of code and citing Data Camp. If you paid for it, is it worth it? Are you learning stuff that you can't find elsewhere, or are you just paying more attention because the info isn't free? All opinions appreciated.

I learned about it recently and thought it looks good. I’m thinking to try and complete their ‘data science career track’ course which is ~90hrs. I just wanted to check if anyone thinks it’s a waste of time or if there are other better options.

I’m a PhD in neuroscience so I’m familiar with experimental design and statistics. My main goal is to become more fluent with python. Thanks