Material covered mostly on the surface level.

They should add more examples using the tools and services, however Iearned a lot of thing related to data engineering an the aws cloud, I think this knowledge is going to be very useful in my professional dimesion

I am only on week 1 but already I have lots of suggestions. This course could be improved by

1. If you use an acronym explain what it stands for.

2. Make it very clear where the gists, github repos are.

3. Some advice provided is out of date or not good advice. Debugging lambdas can be done using other approaches which have zero cost and do not tie you into a specific vendor (e.g. GitHub ). I have left comments in the discusssion forum on this.

4. Improve the explanations and content , testing isn't covered at all well. Why is Pytest ( a dependency) better than Unittest (a cor elibrary) I agree its beter but what if I do not know, what should I test and how. All this wasn't covered and it wasn't made clear I should know it.

5. Improve editing , in some lectures the lecturer is answering questions and there are a lot of gaps between the answers and unheard questions.

6. Imporve the delivery, sometimes the explanations provided are unclear or lack good reasons why the course of action is being taken.

7. Provide more hands on labs.

Wow, lots of lectures that discuss tools without actually a mention of the goal(s), objectives of the tools. It seems almost the entire course lost the forest for all the trees/tooling and doesn't present a cohesive theme of what data engineering is about and tools to support that endeavor.

The course is a mess - there is no continuity, and the clips are basically snippets from different times, i.e. they were not created specifically for this course. The tests are a mess - week 2 tests week 3 knowledge. There is a lot of repetition (been introduced to Cloud9 and Codespaces at least 3 times each) which makes it difficult to concentrate on one thing. the course would be a lot shorter and more efficient if it was filmed with the purpose to create a course, at the moment it feels like just a money-grabbing opportunity.

A lot of reused material, a lot of random stuff and just jumping to examples without actually giving context.

Great introduction to the concepts, very good practical examples, with relevant technologies and platforms.

Need to be revised

Great course

Very important information and concepts was shared.

Very well designed course for data engineering

good

It doesn't provide labs for AWS

no inbuilt labs