Hi everyone,
I just completed Course 1 – Introduction to Data Engineering from the DeepLearning.AI specialization. I’m comfortable with the theoretical concepts, and I have good knowledge of Python and SQL. I’ve also built a few small projects like web scraping for Amazon price tracking, so I’m not completely new to coding.
However, I’m finding the hands-on labs very overwhelming.
A lot of the implementation — like using Terraform to provision resources, setting up the AWS environment, and especially writing ETL scripts for AWS Glue and Lambda functions — is quite challenging.
To be clear, the scripts and infrastructure code are already written in the course. All I’m doing is following instructions: connecting one AWS service to another, filling in endpoints, updating variable names, and running pre-written Terraform scripts. Most of it is clicking through the AWS Console and editing simple config values.
Still, I feel like I don’t understand what’s really happening behind the scenes .
My questions are:
- Will these AWS tools (Terraform, Lambda, Glue, etc.) be taught more deeply in the later courses of this specialization?
- Or should I start learning them in parallel on my own?
- If so, can anyone recommend beginner-friendly resources to learn the fundamentals of Terraform, AWS Glue, Lambda, and Bash scripting?
I want to be job-ready, and I’m committed to learning, but right now it feels like I’m just wiring together black boxes without understanding how they work.
Any help or learning path would be really appreciated!
Thanks in advance