This is a good overview, but I found the lab in the week 4 quite unhelpful. In my view, it would be a much better learning experience if we initially build these pipelines from scratch without the abstraction of a tool like terraform. This is the philosophy you follow in your deep learning specialization which in my view is very effective. Its important to have a clear understanding of each component in the pipeline (ec2, s3,rds, vector db, lambda) individually before abstracting it with terraform. As it stands, I executed a bunch of scripts, initially got a bunch of errors which I really did not understand because I do not as yet have a good understanding of what is happening under the hood. Again, my main recommendation is have us build a pipeline from scratch without terraform.

As someone already in the field of data, this course was pretty easy, but I could see it being pretty difficult for newcomers to understand all of the material. I would have preferred more focus on the labs, and think they should have started with basic data pipelines instead of complicated Terraform/AWS pipelines right off the back. It would have been cool to implement a data pipeline that's usable for a small project without so much reliance on AWS.

Greate lectures; brain-dead exercises. Auditing the course would be the best

The Lab of week 4 is something confusing

I am extremely dissatisfied with my lab experience (Assignment 3): bad coding practices are being implemented, terraform init stopped working propertly, reboot doesn't reset the setup. No support from Coursera.

Worst Practial Labs so far. Doesnt work properly and fails often.

The instructor skipped some instructions. There was also mis-spelling. I will not be completing this certificate through Coursera.

extremey bad, both technology as labs

Disappointed.