Data engineering course
I just got through the data engineering specialization developed by deeplearing.ai. The course is taken through coursera which has some kind of relationship with deeplearing.ai. I have taken many courses on coursera before and overall its a great platform to take courses. Currently the price is $49.00 for a monthly subscription and that allows you to take most courses on the site. You can take as many as you want for the month and cancel after you are done. I usually do an month at time as I find a particular course of study I am interested in.
The data engineering course is here. Its taught by Joe Reis who wrote a well respected book on the same subject.
The track consists of four courses:
- Introduction to Data Engineering
- Source Systems, Data Ingestion and Pipelines
- Data Storage and Queries
- Data Modeling, Transformation, and Serving.
My motivation for taking this:
I read Fundamentals of Data Engineering and liked the structure of the content. I am a big fan of understanding fundamentals and I feel this book did a good job of covering the basics of Data Engineering. While I have done a decent of amount of processional work in the realm of what could be considered data engineering, I never had a formal introduction to the subject and I thought this course would be a great way to do that.
The good parts:
I thought there was a good balance between the fundamental theory and coding exercises. Several tools were introduced , dbt , several AWS services, Airflow, superset among others. I feel there was a good progression from simpler to more complex with most of the exercises. The content also aligned well with the content of the book and the data engineering lifecycle.
The downside:
As with many of the courses I have taken the coding exercises are somewhat contrived and don’t immediately lead to a deep understanding of the tools. There was a lot of copy this and paste it here. Certainly better that just looking at code. I feel this kind of work does build muscle memory and is helpful. Also some of the tools were not really introduced and left as an exercise for the student. This lead to more of a following instruction to finish the work as opposed to a holistic understanding of the content. For me personally I felt much of the content was very introductory and I just did the required graded work. I felt like I spent a bit to much time reviewing stuff I was already solid on. Your mileage may vary.
Certificates are below
Introduction to Data Engineering