Good overview course with pointers for deeper insights

Great course. The lab 3 instance died a few times.

Very good in general. Thanks Coursera and AWS!

Good survey course. Not much hands-on work.

More hands-on exercise should be made.

Good Course, lots of content

Maybe is necessary more labs

great course to learn genai

good introductory course

Good foundational course

Lacks of more exercises

fully satisfied.

very informative

5 is for god

good one!

great

nice

Good

good

good

Good

I took this course because I like the ML Specification of Andrew Ng very much. For me, that was really the gold standard for MOOC. This LLM course was, unfortunately, a bit disappointing. The labs were underwhelming. To me, not really grading the labs looks like the lack of engagement on the part of the authors. I also had technical problems with the third lab -- I think, some issues with hard-coded versions of the packages -- and did not manage to run it at all! I also missed a forum to interact with fellow students and the instructors. I am still very thankful for this course, it is really hard to make one at this stage. I especially liked that authors went into technical details and provided links to the original papers. I see this course as a germ of a future cool GenAI specification. I am confident that the authors are capable of developing it further.

"Intermediate" level in the sense that you perhaps need some basic understanding of machine learning, but this is definitely not a course that challenges you. You get a very high level conceptual explanation of basic concepts (including things like LoRA, RLHF), but definitely no specifics on the implementation level. The assignment "Labs" consists of executing pre-written code in notebooks, and seeing the result output. No coding of your own, and typically just making function calls to Huggingface libraries, but not actually seeing how the algorithms are implemented.

Lots of theory with very little practice. You will not walk away from this course feeling confident that you know how to code any of it. The labs that are offered do not teach you much either. The instructors just tell you to not worry about how it works, and that it just works. The instructors need to add a whole lot more practice code to get you practicing the theory they teach. At this point, I am looking for where I can find that information because theory without practice is pointless.

The course material was all pretty superficial; the lectures never really delve into the nitty gritty details. The labs require no coding, which is disappointing. That being said, it's a good overview of the current landscape. If you want to learn implementation and the way things work (the how rather than the what), you will probably be disappointed.