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!

Hey everyone, just sharing that all 600 of our courses, plus tracks and certifications, are free this week.

https://www.datacamp.com/campaign/nov-free-access-week-2025

Have fun, happy learning!

Done.

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).

And so we go...

Hi all!

I haven't been to the sub in a long time. I started my coding journey when I was talking to my friend about how much I didn't like my current role at a marketing agency and how I wanted to build stuff and actually solve problems rather than focus on presentation and project management. He worked as a Data Engineer at a large fintech company but started off as a analyst. He invited me to his company's HQ and showed me around and explained how he transitioned from being an analyst to a data engineer. He recommended Datacamp as a useful tool to get started.

Prior to this I had always been interested in technology and software. However, I was really bad at mathematics. In my country you need good maths grades to study computer science in university and all software engineering roles want a STEM degree at least so I wrote it off as something I couldn't do.

Using Datacamp I slowly taught myself the fundamentals. I then did my own personal project that grew and expanded as I learn new skills. It started off as a simple notebook file on Datalab but ended up being something I deployed.

I was laid off from my job - I knew I didn't want another marketing job so I did a computer science conversion masters. I still in the program and I had a great time. I enjoyed the masters way more than my History undergraduate because the content was actually interesting.

I interviewed for a big tech company and got the internship. Not going to get into a lot o f details here for privacy reasons.

DataCamp is a useful resource but I think its role is that of a starting point - teaching yourself includes both using as many resources that fits with your way of thinking as well as putting your skills to practice.

Moreover - making the transition is a multi year process. You need a degree, you need projects, you need the knowledge.

Hello guys I was able to complete the practical exam today on my 4th attemp (last one before restarting the process). I'm so happy, I feel obliged to retribute, since there were people that helped me through the comments, let me know if you have any questions.

I recently came to know about DataCamp. Is it a good platform to learn? And does the certification meet industry standards and is accepted by companies?

NOTE: If you end up signing up for Data Quest, please show your appreciation of my guidance by signing up through my link: app.dataquest.io/referral-signup/j58oftwg/ Sadly, one of the drawbacks of DataCamp for learners is they do not have a promotion for referring other students at this time.

I just started jumping into the self-guided lessons for data analysts and scientists. I am writing this article as someone who has just started out in the first weeks of using both programs. I hope this article helps both platforms or programs to improve the experience of using them and also helps students reading this to find the best platform for themselves. One last note, I’m using the free versions of data camp and data quest.

Pricing

So, the first thing I noticed between the two is that Data Quest is double the price of Data Camp. I was surprised by this because it seems as if there is actually more content on Data Camp. Currently, the price hasn’t mattered yet because I’m using the free version but the only reason I wanted to use either platform was because of the cost savings compared to Udacity and flimsy video-centered programs like Udemy, etc. The major downside of DataCamp is that they don’t allow for a month-to-month subscription, which is pretty essential when you are first dipping your toes into a new field and new material. DC really overlooked the fact that many people are trying to find out if Data Science is right for them, so why would they commit to a year-long commitment after a few lessons.

Free Content Allowance

The first issue I ran into though was that Data Camp only allowed you to complete one section at a time each day for the free edition. I haven't had this issue with Data Quest so far but their sections tend to be a lot longer to finish. Either way, this is not a big deal for Data Camp because I could go to the other program after and so I did. So far using the free version I have been switching between both when I reach the content limit, meaning when I reach the limit on DQ I go to the other platform. It also helps to get a feel for which platform is better for you while it also helps you retain info by practicing in both.

Quality and Thoroughness of Lessons

However, almost immediately I ran into the problem with Data camp that the lessons were not thorough enough. I got stuck in one of the first sections so I had to go to Data Quest to look up the section and complete it there. In the variables section for Data Camp I got lost trying to figure out how to solve the “Operations with other types” section because the video and walk-through didn’t point to a specific way of handling the situation. Data Quest seemed to break down the material a little more at least in these first sections. This also might mean that if you are not new to this material Data Camp might be a better program to update yourself. One additional benefit of DataCamp is that it is gamified, leading the users to think maybe it is a little bit more of a mature platform overall.

Overall Design and Maturity of Platforms

Overall, it was far more thorough and fully designed in Data Quest. Also, I ran into a different issue with Data Quest, primarily that they didn’t have a mobile app. I knew that I would constantly have to be practicing if I was going to be able to learn. This forced me to use both programs with discontent overall for both. It is also disappointing that it costs more and doesn’t offer an app. You could use on your browser but it’s not as accessible still and again the higher price seems like they increased the price before they were clearly more competitive. I think the business planning could have been better and they could at least offer better discounts than just being the same price at Data Camp when they aren’t on sale. Currently, Data Quest at full price is almost four times the cost of Data Camp ($150 vs $600) when not on sale vs. Data camp on sale. Data Camp offers a very competitive rate and offers this discount often, meaning it is clearly a more affordable option.

Final Decision

If I had to make a decision between them both, which I may at some point I would probably say to use Data Quest because the main point is to learn and I got stuck in Data camp. Data Camps seem overall like a more mature platform that only needs some development of the curriculum for beginners. I am going to hold off for now on buying either because Data Quest’s price is far more than I think is worth it to pay for. I might just do the $420 intro program at Springboard or Udacity instead because their programs are more respected anyways. The high price also defeats the purpose of why I originally went this route for the reason of being self-guided and saving money. Overall, I think both Data Camp and Data Quest need to seriously consider the issues I pointed out here because I would actually say it would be better to start out elsewhere until they fix these issues.

Update: I have contacted DataCamp and DataQuest to do a comparative write-up about the two platforms to help them improve their platform, so far DataCamp sent a generic response back about how they aren't offering any partnerships of this kind at this time. DataQuest responded to my feedback and forwarded it to their team but I haven't heard back about my offer. I can say at this time that DataCamp seems less likely to think outside the box in terms of improving their product and am disappointed they haven't considered my feedback.

u/richie_cotton from r/DataCamp responded:

Thanks for the feedback on DataCamp and the comparison with DataQuest.

“I'd like to clarify that it is possible to subscribe monthly. While the pricing page emphasizes the annual plans (because becoming an expert data users takes longer than a month), when you click subscribe you have the option to choose a monthly plan for both the Standard and Premium packages.

I'm curious about when you got stuck on the "Operations with other types" exercise. Did you manage to locate any of the built-in help features like autograder feedback (when you hit submit), or hints, or video slide review?”

My response to Richie above:

Yes, I was able to use the Autograder feedback and the answer reveal. It felt like it was as help in pointing out how to solve it, so many times I remained confused if J was stuck before.

u/richie_cotton from r/DataCamp second response:

“Your review stimulated some good internal discussions, particularly around the language on the pricing page. You made a good point that it's currently a little tricky to see that monthly pricing is available.”

u/awaymsg explained three issues I had with Data Camps problem sets, basically that you don’t get granular enough support when solving problems or writing equations. This problem does persist with Data Quest as well sadly.

Did you manage to locate any of the built-in help features like autograder feedback (when you hit submit), or hints, or video slide review?”

My biggest issue with Data Camp's autograding feature is that the helpfulness is kind of inconsistent across different courses. The hints can be helpful and force you to think about the problem differently, which does sometimes lead to me figuring out the correct answer, but sometimes I'll get completely stuck due to a syntax error or something silly, and I feel like there's no help at all aside from replaying the video to look for the example the presenter gives.

By biggest gripe, though, is when you "show answer" there's no possible way to re-attempt the problem. Not that I want to get any extra points, but I think it would be really helpful to see the solution and then write the whole code again from scratch. Also, some sort of highlighting feature to see where exactly I went wrong would be nice.

Hi, so a quick background about me - I have 2 degrees in statistics from good universities, over 6 years in data analytics in the industry. I am currently a digital nomad and I currently do some freelance work on Fiverr as a pro and top rated data scientist and analyst.

I am using Datacamp mainly to sharpen my skills and to remember some stuff I forgot along the way. There are also some stuff in llms and deep learning that I haven't used much so it is nice to do it in datacamp. Also the data engineering and production courses seem to be interesting.

To gain more theoretical understanding that datacamp lacks, I usually use the O'Reilly platform and books.

The code alongs section has also some great stuff there. Also the blogs.

"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?"

Has anyone done both or currently enrolled? I’m in The Google DA coursera and enjoy it but was wondering which would give me more value when it comes to the job market?

When solving an exercise using the Datacamp way (starting with a lot of 'base' code), I usually can solve it quickly and easily without paying much attention to what I'm trying to accomplish or how. The next day, I can hardly remember what I learned.

By deleting all proposed code and starting from scratch, I have to think carefully what I'm trying to do and how. It takes much longer, but you have to use much more information and also what you learned before. This way I can also retain much more of what I learned.

Usually, the autograder will complain because you'll use other names. But look at the query result and check if the result is what you tried to accomplish (similar to a real-world situation). After that, copy your solution to some text editor and reset to sample code in order to see how the datacamp teacher solved it.

We’ve been working on something big for a while, and as of today, it’s live!

We’re calling it our AI-native learning engine, and the idea is simple: every course on DataCamp should adapt to you.

Not just “AI assistant on the side” adapt.

But actually change the way you learn, pace, examples, explanations, based on your skill level, role, and how fast you’re progressing.

So if you’re new to SQL, it might slow down, simplify examples, and guide you through core concepts.

If you already know the basics, it’ll skip ahead, push you into more complex queries, and focus on areas you’re actually trying to get better at.

It still feels like the interactive, hands-on DataCamp experience you already know, it just legit feels smarter.

No static videos. No robotic chatbot pop-ups. It’s like learning with a teacher who actually knows what you need next.

We built this after acquiring Optima, a company that specialized in adaptive AI learning tech. Their founder, Yusuf Saber, just joined DataCamp as our Chief AI Officer (and he and our CEO are hosting a live webinar on Nov 17 to go under the hood on how it all works - lmk if you want a link to that!).

If you want to try it: https://www.datacamp.com/learn/ai-native

I understand that you probably have to do a lot of the projects that are available and some projects on your own to get "really good"... But I feel datacamp can be a great base of knowledge to get really good at coding. What do you think?

No crazy long story here. Just wanted to put this out into the internet ether in case anyone was wondering "If its worth it" to get one through Datacamp. It wont nail the job for you, as most (all?) companies will give you a coding round or two, but it looks good on the resume and will help you get through the ATS filters.

I'm thinking about getting a DataCamp subscription, but I'm not sure if it's worth it with how fast AI is changing.

A lot of the courses focus on specific tools/libraries, and I'm wondering if some of that knowledge could become outdated pretty quickly as AI tools keep improving.

For anyone using DataCamp recently: do you still think it's worth the subscription? Or would you recommend learning through other platforms/resources instead?

Just looking for some honest opinions before I subscribe.

I’ve been working through the DataCamp track for the Data Engineer Associate certification, and the courses and exercises felt very structured and approachable. I breezed through most of the material and felt like I was building confidence along the way.

The actual certification exam felt like a completely different world.

The exam covered areas that weren’t emphasised much (or at all) in the courses leading up to it. I went from feeling well-prepared to feeling like I’d missed a huge chunk of what they expect you to know. It seemed like the track only prepared me for a small portion of the real assessment.

Has anyone else had this experience? How did you bridge the knowledge gap between finishing the content and actually being ready for the certification?

Also: the practical exam says it’s 4 hours. Is that a hard time requirement, or is that just the maximum and most people finish earlier? Curious to hear how others managed it. Thanks!

UPDATE

I just completed the practical exam in about 60-90 minutes. I would highly suggest reading up on both `COALESCE` and `WITH`-queries. They ask you to clean data, but all the tables are read-only, so you need a way to combine and clean tables without altering the actual data. The two keywords mentioned will help with this. You will also need some conditionals in your queries, so also have a look at `CASE`.

Hey, anyone studying python on datacamp? I am looking for study buddies/ accountability partners. Not too many people, just few who are able to commit to studying python most days a week, even if that is for 15-30 mins a day.

Timezones don’t matter because we don’t study together but post an update daily on discord about what we studied.

I already have a small study group for SQL in the same discord server and our daily check-ins have really helped us stay consistent. So want to have a similar group for python.

Please connect only if you can commit to studying python, at least for the next 100 days.

Hi all! I just started the associate data scientist with python career track and I think it was a great decision, so I want to share my initial experience and the resources I've found so far. Also, if anybody is taking that too, it'd be cool to share resources and ideas along the way.

My background is management and english is my second language so I may be taking a bit longer to grasp coding but overall I don't find the career track too challenging yet. I like that it gives me a lot of courses that can be taken sequentially, that way I can avoid the (huge) decision fatigue of having to pick and choose courses, books and projects along the way.

For context, I went straight to data science even though it's harder than data analysis for me because (1) it seems more intellectually and financially rewarding on the long run, (2) I don't think it's a good idea to make a lot of effort to get a data analyst job so I can make a lot of effort again to get a data science job, it's just overkill for me, and (3) because I think that, in the long-term, if I don't use it in my regular jobs, I'll still be able to do way better with masters or PhD research.

For data-related careers, to me, datacamp seems like the best option so far because the yearly subscription is not very expensive (monthly can be costly though), it's very interactive so I don't get bored (MOOCs are the death of me, I get so bored that I become restless and start doing something else), comes with suggested projects that will allow you to actually learn and to showcase your skills (a lot of those on the python track) and you can even get certified with no further cost.

I got the $1 for the first month promo so that was nice but honestly, if you're considering a data related career path seriously, I'd recommend you just pay the full year and get done with it, there are way worse options out there.

There are tons of online resources to supplement your learning, and a lot of them are free. I actually started with one I would recommend if you want to learn python interactively, https://pythonprinciples.com/purchase/, because they usually charge $29 but apparently they're giving it away for free these days.

I've found additional resources (lots of free stuff) on classcentral's best course guides for python and data science (there are guides for AI, machine learning, applied machine learning and calculus too), and on a few youtube channels: alex the analyst, sundas khalid, and python programmer. I haven't tried kaggle yet, but it seems like the go-to tool for getting started with project building. But keep in mind that I wouldn't sweat it with the additional resources at the beginning unless you need those to actually grasp the concepts or to drill them into your head with extensive practice.

Also, I just ask chatgpt for exercise answers, to correct my code, or even to explain solutions step by step if I struggle with something. It's been working wonders so far.

It seems like I'm promoting datacamp but honestly I'm just happy that I found learning materials that allow me to overcome procrastination and decision fatigue. So that's that, feel free to leave a question if you need a hand with something, good luck!

I just completed the Data Engineer and Associate Data Engineer tracks and am currently working on the Professional Data Engineer track. I'm curious—has anyone landed a job through these certifications?

Would anyone here be willing to help me figure out with what I possibly did wrong? I can’t find it out no matter how many times I try to double check each column.

I’m done with all the other tasks and they’re correct, but I’m stuck on this one. It says error with “Task 1: Clean categorical and text data by manipulating strings”.

I’m guessing the warranty_period column has the error but I can’t figure what else I need to do because I think I already accomplished the criteria.

Thoughts, please? :(

I just wanted to say that I much prefer the older design. The colours of the new design are too high contrast.

The only way I can understand this is maybe there was some legal reason they couldn't continue with the original design and they had to make a new one in a week.