Everyone Grows Out of DataCamp, Use These Platforms Once You Do
DataCamp helped me get an A in my programming class, but I grew out of it and unsubscribed.
As we all can see, the data field is rapidly growing. People all across the globe are intrigued by the importance of data and eager to learn about it. Nowadays, you can find a lot of data courses online, making learning data science accessible to people. Among all the online learning platforms, one of the top ones is DataCamp.
I used to be an avid user of DataCamp myself. For reference, I even accumulated 239,910 XP and completed 43 courses. I still remember all of those days trying to understand data science by marathoning through all the videos and coding practices. However, I stopped doing it now as I “grew out of it”.
“Then, was your subscription worth it? Did you regret it?”
If that’s your question, I don’t! DataCamp helped me a lot. I even recommended this platform to lots of my friends. Here are the cons I feel DataCamp provided.
1. It has short videos with great intuition and materials, making it beginner friendly.
DataCamp videos are intuitive. They explain programming syntaxes in a detailed manner despite being short videos that help new learners stay engaged. Those videos also have statistical and computational theories, which helped me understand more about the material. Some even said that those materials helped them ace job interviews!
2. Lots of basic hands-on coding exercises
Programming skills are a form of practical knowledge. No one could be a good programmer just by reading and understanding the meaning of syntaxes. Instead, someone who aims to be a good programmer should familiarize themselves by writing code. DataCamp is a good platform for this hands-on experience. Coding exercises follow the learning videos to get learners a real feeling of writing code, in a fun way!
This feature of DataCamp made me understand the basic syntaxes in R and Python easily. I still remember sitting in my R programming class and seeing my friends being overwhelmed by the amount of R syntaxes introduced. Thankfully, I learned those syntaxes enjoyably through DataCamp before taking the class and pretty easily got an A in the end!
“Then, why did you stop subscribing? What does it mean to grow out of it?”
Despite helping me get familiar with some programming languages, I feel like DataCamp is not good enough for long-term learning. I don’t think you would get a job just by DataCamp-ing all day long. It’s only for beginners and here’s why.
1. DataCamp makes you dependent on their pre-provided syntaxes
To work in the data field, you must have strong programming logic and learn how to write syntaxes from scratch. DataCamp practices are mostly fill-in-the-blank types. It did familiarize me with the structure of a programming language and the syntax included, but not more intuitions. I still need lots of practice when I write code from scratch. The good news is you can train your programming language and syntax writing using HackerRank once you get a hand with your newly learned programming language.
2. DataCamp doesn’t teach you to choose the right method to solve a problem. It doesn’t give you space to explore either
The guided projects and hands-on exercises should answer the arranged problem in a certain way. When learning in DataCamp, they would tell you to use a specific approach to the problem, with no space for choosing methods or exploring. However, as a data scientist or data analyst, you’re supposed to know how to choose your approach for a data problem. Even though I learned a lot of methods and syntaxes from DataCamp, I found it hard when I first tried mining a raw dataset. If this is also your case, it’s time for you to turn to Kaggle. Using Kaggle, you can learn people’s approaches to analyzing raw datasets through their published notebooks and even make one yourself!
3. Even after learning, DataCamp doesn’t give you anything credible enough to show off
DataCamp provides a statement of accomplishment upon course completion and certification upon test. However, DataCamp statements of accomplishment and certificates aren’t associated with big companies or universities, unlike Coursera ones. As for projects, DataCamp only offers guided projects to work on. These don’t allow much modification or creativity in our work. Rather than making projects in DataCamp, I would recommend using Forage to get project ideas. Their virtual internships are the best “guided projects” that can help you become more creative while honing your data skills.
“So, what’s the conclusion?”
I encourage everyone to use DataCamp to start learning a new programming language or software. However, once you get familiar with that new language/software (alias grow out of DataCamp), you should move on and hone your skills through other platforms.
