The videos do not provide any information about what a vector DB is and how it works (e.g. the architecture), same for RAG and LLM. The project is extremely trivial and, personally, I won't put it into my personal repo because it won't add any value to it (possibly the opposite though).

Needs testing on Windows. Final project didn't provide a cloud option and I could not get it to work locally. Probably a much better experience on Macs supporting Cuda.

Outdated and too little information for each step

I thoroughly enjoyed working on this project. Initially, I was caught off guard by the tight two-day deadline, as I didn’t have the capacity to complete it in that timeframe. However, I decided to pause and reset the timeline for the following week, which allowed me to complete the final quiz successfully!

The introduction to the lab was good, but the goals could have been more specific. I would have liked more time spent on some of the concepts that the final questions were about, though that may be in a different course.

The guided project helped me understand RAG and its application in a concise and accurate manner. The project code was very helpful in understanding the workflow of implementing RAG with LLMS.

It was a good entry point to the RAG's world, I hope to see more professional courses too.

The project is easy to follow for an experienced developer.

Good Exercise for introduction RAG by LLM and VectorDB

4 stars only because of difficulty getting the Jupyter environment working. Instructor was amazing and informative. Will be signing up for more courses!

Was expecting something a bit more comprehensive.

The course provides a good introduction to the topic, but without explaining details of the code and used parameters. Also, the repository is outdated and requires tweaks to make it run without errors.