A detailed comparison of DataCamp and Code Academy for learning programming skills online.

Twice I had a stroke of good luck and got Tableau and Power BI training on the job. But as soon as I applied for Python or R positions, the employers wanted rather a skilled worker.

I started to expand my programming skills, while I still worked with Tableau. I learned SQL first, since Tableau was getting data from a MySQL server. Alongside it, I taught myself a now mostly forgotten data mining tool, RapidMiner.

I began to feel secure with all three, as a colleague showed me something that he built with R Shiny. That blew my mind. R seemed like all three in one and for less money. I decided to learn R programming.

My favorites

I mainly used Code Academy and DataCamp to learn R and Python.

Code Academy helped me to build my first small Python app. The app would have no use, but the speed of learning and coming to a visible result encouraged me a lot. I also did a few basic SQL courses with Code Academy and I loved the practical tasks that followed each chapter.

At the time I was active on the platform, DataCamp used to separate the main learning path from the practical exercises and so-called projects. I must confess I never started any of them. They were one click too far. It made a difference since I did this learning during the week and each spared effort had counted. For this reason, DataCamp seemed a bit theoretical to me.

Fill the gaps technique

Both platforms share the same feature: the gap-filling learning technique. I rather assess it as two-folded. You watch a short video and then you get to a piece of code to only fill in the gaps. The gaps are basically the new functions the video was about.

It sounds like a very good learning concept. My progress was unbelievably fast, but it soon began to feel like a conveyor.

You write the complete code only in the beginners’ courses. When I arrived at the advanced ones, I just had to type in a couple of functions. The whole bunch, up to a few dozens of lines, were already there.

I caught myself at scanning the code and semiconsciously hitting the keyboard. I stopped thinking and memorizing new things. But this somehow taught me to read very fast through the code. It was good for the future when I had to deal with long and badly organized queries or scripts.

A good video makes a difference

During the days I was learning Tableau, Power BI, or later Salesforce, I used to fill my browser history with thousands of URLs. Most of the videos I clicked away after the first ten seconds.

I see no reason for recording a 30-minutes PowerPoint presentation or the movements of your mouse. Such things can do better for me in a text form with a few screenshots. In a text article I can easier get back to the part I need to repeat.

If a feature needs more than 5 minutes to be guided through, it is more than one feature actually.

I want to give an applaud to videos and coaches from Code Academy and DataCamp. Just a three minutes lecture with a few essential visuals and a function explained in a nutshell. And right after it, you get to coding.

Before DataCamp I never thought that the visual presence of the coach in the video can be so important for learning. But it created a lot of trust to virtually meet the person behind the course. And I saw no “talking heads”. The videos combined a TV reportage style with a small presentation.

Selecting useful courses

The career and skill tracks are the other thing I loved about both platforms. As a student, you could either pick up a course compilation for a job profile, or a compilation for getting a particular set of skills. The skill tracks could be job independent, or just on the contrary, very job-specific, like doing data analysis for a financial institution.

When my progress reached the advanced statistic part, the coaches surprised me with the short and well-shaped explanations of the basics that we were going to build our code upon. Still, it was no statistic course and the relevant knowledge remained an important prerequisite.

The courses were not made for the ultimate dummies. That increased their value for the serious learners.

“Good girl!”

DataCamp and Code Academy reward your smallest learning progress with either points or badges. This cute gamification had an encouraging effect, I must confess.

At the DataCamp I reached 145,911 points, — sounds wow, isn’t it? — and had 32 completed courses behind me within the 12 incomplete months. I paused my subscription a few times.

Till then, I managed to finish a Data Scientist with R career track. I found myself somewhere in the beginning of the Python data science track, when the intuition told me that theory is not enough.

A short afterward

Still, despite all quirks, the online programming courses gave me a strong understanding of an abstract script structure, of the nature of things you have to think about before starting to program. I nevertheless supported my learning with some offline practice. That I would like to cover in a separate post.

Somehow later I tried to learn Python programming packages for mobile devices without any course materials. I ended up with an app that worked with so many “ifs” inside and outside it that I could never release it.

Online programming courses do not teach, they rather guide you. I do believe that the courses I’d finished were a good mixture of theoretical tips and inspiration for practical use.

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