A Year Of DataCamp Taught Me NOTHING | DataCamp Disaster: How I Wasted a Year of My Life

Are you considering DataCamp as your go-to platform for learning data science?

[ArturDragunov]

I've just recently finished their Data Scientist Professional Career Track and I was very satisfied with it. Indeed, datacamp is not the place where you can learn theoretical concepts. If you want to learn those, search for youtube videos, articles or go to the university at the end of the day :D. As I feel, datacamp is more about implementation of the concepts. As I have solid theoretical background from my master's studies this track was just as a quick learning how to put theory to practice using Python instead of R, which is usually used at statistical classes. So, depending on your initial goals, datacamp can be a good or a bad place to learn.

[daveebbelaar]

I've never used DataCamp, but I recognize what you're saying about learning things in a "vacuum". The concepts just don't stick that way. Nothing beats real-world practice, working on actual projects.

[FullRewardMinistries]

Here's my experience with it so far. I've spent a lot of time developing proper study techniques, and learning how to learn. DataCamp works REALLY well for exposure, and showing concepts that you should learn. What I'll do is do the exercises, practice them, and write down the concepts. After I'm done I'll take a random DataFrame and start using the skills they taught in a HANDS-ON project. If you start with the right courses, they DO explain topics like libraries, but there is a lot of assumed knowledge. There are ways to make Data Camp work well for you, but if you're truly a beginner, chances are you won't learn it the way you should. I already had a lot of my study methods planned out, and had a lot of understanding to begin with.

[ManWhoDoesNotCare]

Some of the problems described can be solved by working with projects related to the course material (a longer, larger assignment with analysis of some data sets, etc., from start to finish) and then entering competitions. I use DataCamp with some programming background and it definitely helps. Overall, nice summary!

[GuppyPal]

I have done a lot of online learning across a variety of platforms. In almost all cases, you can roll your way through the material only half paying attention and still finish with the cert. It's important to try hard to really pay attention as you go and genuinely learn the stuff though. If you have your own work or projects to do on the side in addition to the online learning, it makes things a lot more meaningful, and the content will still better. Just my two cents.

[balford]

Great video. You don’t know what you don’t know. This very useful for people starting.

[theclintwestman]

DC is actually very good if you have the right expectations. I wanted to gain familiarity with the topic of data science and some of its specific tools. And I'm pretty satisfied with the structured learning path. I already have many yrs as a pro developer, so I get a lot of mileage from an overview. In my current job, I'm already applying the things I"ve learned.

[elbachirelkharfi]

i have been using DC and you are right, but it is really good place to start
the solution is to work on personal projects and rewatch videos to understand concepts
overall a 7 out of 10

[tristanmeijer]

As someone who spent 80 hours on the Datacamp course for data scientists, I can relate to this video. It only helped me because I work with R and SQL for my job but most of the knowledge I obtained is lost due to some of the reasons you described. Then again, that happens to most knowledge that is obtained but not used, right?

[binry_dstructr]

I never used DataCamp, but almost my entire AI/ML/DS curriculum was self-designed and done through Udemy. The courses I took combined coding, theory and projects in a way that not only taught me what to do but why I'm doing it. Thus, I actually use the materials learned on my job. My first machine learning project at work is made up of code snippets Frankenstein-ed together from various projects from those courses. I'll always plug Udemy or at least the specific courses I took. They literally helped me switch career paths.

[mbmathematicsacademic]

DataCamp has been absolute great for me. The reason is because I am more familiar with 90% of the theory for things they teach. In 2023 I spent an entire year coding with Python only and working with Numpy, Pandas and Matplotlib. Moreover in 2023(my final year) statistics I did Sampling Theory, Linear Regression, Time Series and Statistical Analysis for Experiments as individual modules at Varsity. I did Stats for 3 years, hence I enjoy it more than anything because I also do projects after learning. And to be fair, I agree with you, it's not that good for someone who doesn't know fundamentals and statistics

[yihdegawgebreal]

great advice. I would like to appreciate you for putting this much effort to make us clear with data camp

[qumbermurtaza]

I really like your analysis it is very insightful and truly reflect some of the loopholes in their courses but I would say your course selection wasn't too ideal if you didn't have any prior experience about the data analytics you should have choose the data literacy track it will help you make your fundamentals strong and when your fundamentals are sorted you can easily grab the practical and theoretical concepts quite easily. And I can assure you DataCamp user interface is one of the best in the industry because I have done some courses on Udemy and Coursera they are too tirelessly long and sometimes irrelevant as well so it's very hard to keep focused and motivated throughout the courses.

[marvinbulahan]

I love datacamp's style. The points he talked about are true about the shortcomings of the courses offered because it focuses on the technical skill. I realized if I also started on Datacamp without prior Knowledge I would have had a very shaky foundational understanding. But luckily I finished Coursera Google Data Analytics first before Datacamp. Coursera courses lack the same amount of application like Datacamp, and Datacamp courses lacks the same amount of theoretical knowledge, concepts explanation and giving real work scenarios as Coursera. In the end I think one source won't really be enough.

[mamdouhdabjan]

I would suggest some Coursera courses that I feel really address the problem.
Google's Python crash course.
A single course. You learn the concept and go the exercies and bam. A task that requires so much thought(at least for me) that uses a simple concept like a loop. Even though I took this course after an entire Python specialization, I felt like it solidified the ideas more than that entire specialization.
Python 3 programming specialization by Michigan University.
Again it addresses the problems you talked about. After learning the concept, you go to a lab where you do like 10 different exercises on the subject. I would recommend that people take these courses/specializations because they greatly helped me with learning.

[melainenyuyfoninsaikila]

Interesting take. However, I do think like most learning, the key is practice practice practice... Datacamp provides the basics, if i may. On that foundation, you build.

[EntertainmentEncyclopedia]

Thanks for this video. I’ve been trying out datacamp off and on for a year in the hopes of going into data analytics from my current, non-tech job.

[ron]

If youi want to write a novel, you can't spend all your time reading grammar books. But that's how many online courses are constituted. The courses should be made up ONLY of projects, progressing from simple to complex (you can learn the rules and syntax as you go), so you get a better understanding of how to code in the real world.

[imyhull]

Totally agree. Everywhere is pushing short bootcamps and these online courses and I am being told that my MSc in Data Science is pretty useless in comparison. This is rubbish as I learned so much during my degree, mostly from my own research and working and struggling on individual projects and testing myself. I had a base level of knowledge of basically zero having no coding background. The bootcamps and short courses are so shallow in comparison to this experience.

[AllinXavi]

As an aspiring IT professional that wants to get into data, this is refreshing to hear from another person about their struggles in self-learning. I have feelings of regret for using online resources such as data camp to learn data as a way to teach myself only to end up hitting a dead end the moment I had to start creating my own projects.

I spent nearly 5 months on this and it definitely feels like I wasted my time since I am planning to get into a more generalized IT role such as help desk instead of getting into data right away just to get my foot in the door in IT. I wish I did this right after graduating from college if I had known the competition for entering data science is tough.