Review of Data Engineer with Python – Datacamp Course

Review of Data Engineer with Python  – Datacamp Course

I recently wrapped up the Data Engineer with Python course on Datacamp and thought I would write up my thoughts on the course and if it was worth the massive amount of time I invested in it.

The course promises a lot! –“Start your journey to becoming a data engineer and gain the in-demand data engineering skills companies need. In this track, you’ll discover how to build an effective data architecture, streamline data processing, and maintain large-scale data systems.”

I love the look and the feel of Datacamp it’s a slick looking website and the videos are top end in terms of production quality. I like the idea of earning experience points and trying to maintain a streak basically pushing you to form a learning habit. I managed to notch up over 90K experience points and hit a 88 day steak during my time on Datacamp which looking back at I’m pretty impressed by.

What I like

  • The look and the feel of the website.
  • The quality of the videos are high end.
  • The instructors are experienced and knowledgeable.
  • The lab environment is fantastic never had any issues apart from the Spark courses taking a few minutes to load up, but that’s understandable.
  • A structured approach to learning starting of with Python, SQL and building up to things like Airflow and Spark, but VERY high level.
  • The real world datasets you get exposed to, but it’s hard to actually interface with them because Datacamp does all the coding for you.

What I don’t like

  • You don’t build and pipelines from scratch?
  • All the code in the labs are coded for you. You just have to fill in the blanks? In my mind you don’t learn that way.
  • If you are looking for in depth courses this isn’t it. Most of the video are under 5 minutes normally 4 per subject so 20 mins to teach you Database design? never!

Do I think you would be able to pick up the skills needed to be a data engineer with this course alone? no. If you are starting out in the world of Data Engineering and have no background in tech this is the course for you, your hand gets held the whole way even to the point where you don’t even need to think.

Did I learn anything? for sure I picked up a few things, some of the courses were way better than others (Data Processing in shell springs to mind) and got exposed to how other people implement pipelines and write code. I enjoyed some of the theory and the datasets you got exposed to, but sadly that’s about it.

Conclusion

Would I recommend this course? the short answer is no. The long answer, I would recommend this to someone who has zero exposure to Data Engineering principles and practises. If you are starting out in your data journey and want some some theoretical and sample ideas of how things are done in the real world this is for you. Ultimately don’t waste your money. Jump on to YouTube and find some practise Data Engineering project where you can build out pipelines yourself. Where you can struggle and learn how to solve problems yourself. Only then will you really learn.

If you looking for a good Data Engineering project I highly recommend you check out Darshil Parmar on YouTube who has a few beginner projects where you can actually build out pipelines this will set you up to start building out your own pipelines and projects, or if you want to get really hands on with Pyspark check out Frank Kanes course on Udemy.