Excellent! This class is great for many learning styles and includes lots of visual information and extremely well-planned lectures. The labs top it all off with experiential learning; the labs are well-explained and designed. They are understandable for many levels of learners and bring all the previously learned lecture information together. The lecturers are all fantastic- with information that builds making it accessible. This is an excellent course. Thank you to all those at AWS and Deep Learning AI who designed this class!

A great foundational course.

This course teaches about things like: Instruction fine-tuning, FLAN, PEFT, LoRA, RLHF/RLAIF, PPO, PAL, RAG, ReAct, optimization and lifecycle of LLMs.

The 3 labs use Hugging Face transformers and cover prompt engineering, full fine-tuning, LoRA fine-tuning, and tuning with RLHF to reduce "harmfulness" of responses.

Studying of this course should be accompanied with study/overview of research papers, since the LLMs area is rather advanced; the course includes quite a few such references

Awesome course. The scope and how it was explained was exactly what I needed. Having some explanations by Andrew Ng in some of the intros gave me an extra enthusiasm boost. Not having done any programming for a couple of years, the mild and guided hands-on practical sessions with the jupyter notebooks gave confidence. I review the excellent course material from time to time as a reminder and refresher. I hope this course will be updated from time to time and extended with extra, aligned accompanying courses.

I've been thoroughly impressed by the depth and quality of the material. Generative AI AWS team covered cutting-edge advancements, providing insightful references and practical exercises that act as a stepping stone for further exploration. Each exercise masterfully clarifies key concepts, while seamlesly integrating hands-on learning with AWS SageMaker. By the end, you not only feel confident in your Gen AI & LLM understanding but also gain impressive proficiency in SageMaker's powerful tools.

It was an amazing learning experience - a short yet intense journey into the world of Generative AI.

The course content was excellently organized and presented, making complex concepts easily understandable for learners like me. The three labs provided invaluable real-world experience in effectively using large language models.

The course creators and presenters demonstrated immense expertise and enthusiasm, which made the learning experience engaging and thoroughly enjoyable.

Thank you

I recently completed the course on Generative AI with Large Language Models and found it incredibly useful. The course provided a comprehensive overview of the topic and the instructors were skilled at breaking down complex concepts in an easy-to-understand manner. The hands-on exercises were also helpful in solidifying my understanding of the material. Overall, I highly recommend this course to anyone interested in learning about Generative AI and Large Language Models.

Amazing and up-to-date course about the most fascinating field of LLM use cases and potential.

I'd be glad if there will be a next-level course, that will go deeper into the actual design and 'how-to' options of the mechanisms and systems that were discussed (somewhat briefly) in this course.

Many thanks to the great team of instructors, and for the infrastructures that enables us with actual live labs on AWS systems, in tons of relevant and up-to-date reading materials.

You don't need to be an AWS user to benefit from this course. Clearly presented, SOTA & Great content on the latest LLM application developments!.

Special focus & in-depth around three key LLM themes within the Generative AI Project Life Cycle. With lot's of insightful implementation gems & details!

Themes: 1. Instructional & PEFT Parameter Efficient Fine-Tuning. 2.RLHF Alignment to Human Preferences. 3. LLM-power Applications that combine Reasoning & Action + "Tools".

This "Generative AI with Large Language Models" course is outstanding. It delivers an in-depth exploration of generative AI principles and applications with exceptional clarity and structure. The instructors demonstrate extensive expertise, offering valuable insights and practical examples that enhance the learning experience. This course is highly recommended for professionals and enthusiasts aiming to advance their knowledge and skills in the field of AI.

The “Generative AI with Large Language Models” course provides a good overview and solid engineering understanding of the LLM architectures while building some intuition regarding the Generative AI project lifecycle. It's quite technical, and some general knowledge about Machine Learning (esp. RNN/Transformers) will definitely benefit the learning speed. There are practical labs in AWS SageMaker as well - roll out your sleeves and recall some Python!

This is a great course to get up to date on the current status of the field of LLMs. Even if you do not intend to develop LLM products yourself, it provides you with an intuition of their inner workings, application areas and challenges. Oh yeah...and listening to LLM challenges makes you realize how amazing we human beings are. Regardless of the impressive progress in this field, let's continue to be what we are best at; being human. :-)

This course is short enough that I could complete it in my spare time, yet long and pragmatic enough that I'm now able to take the next steps applying what's presented. I appreciate that I was given resources to dig into the science behind numerous topics, but only required to watch and read summaries. Finally, I found the lecture notes and slides useful when talking with my colleagues about this information.

It is a great course and really taught well. A special thanks to all who were involved in developing this course and breaking down a complex subject into a relatively easily understandable subject. It will be great if further modules are added in future to this course specifically examples of using LangChains and a project which executes an end to end real life toy example. Thank you for sharing knowledge.

Excellent course for anyone looking to dive into #GenerativeAI . It offers a comprehensive understanding of #LLMs, guiding you through the entire project lifecycle of building Generative AI applications. Additionally, it covers some of the limitations and risks associated with Generative AI technologies, offering valuable strategies for identifying and overcoming these challenges. Highly recommended 👍

This course is an effective way to learn about LLMs. Whether you are a hands-on practitioner, team leader, or thought leader, this course will give you the high-level perspective and the details you need to build real LLM-based products. The instructors are well-spoken experts on LLMs. I came away ready for me and my team to work with LLMs immediately. This is one of the best courses I've taken!

Loved it! Generally speaking, it's very well structured, and the instructors were very engaging and clear. However, I wished there was a bit more in-depth guidance through the labs. I'm sure that for someone with experience, it is fine, but for someone not as proficient in the coding department, it would be helpful to hear someone dissect the code. Really explain it. That would make it perfect

One of the most engaging courses that I have gone through on Coursera! Topics are covered in adequate depth, and the labs help to cement conceptual underpinnings of the course material. The course instructors have done an excellent job in keeping the material engaging. Week 3 is a little information dense, and with new developments in the field of LLMs, a Week 4 may be warranted in the future.

The course was great! It presented all of the algorithms and complex math in very intuitive and easy to comprehend ways, and I loved that it had a lot of focus on implementation, use cases, and deployment for practical usability. The labs were great, but they were mostly follow along. It'd be nice to have to do a little bit of the coding ourselves as well to truly feel like we're involved.

Even though this is a harsh beginning course for non computer science people, it encourages everyone to participate to the world of AI of all types, and explains very well and detailed how to fine tune your skills and specialities to make progress using LLMs. Regardless, if we will or not use AWS service, it opens a good opportunity and window to get good profit out of it.

This course provide very good Gen AI materials and it prompts me to starting to dive deeper into understanding low level knowledges like embedding and tokenizer stuff. I wish they can pick a smaller model that would allow users to use small machine to do pre-training with some optional data and some quiz questions & selections can be rephrased to make them less confusing.

It's a great course and very actionable material.

While I like AWS a lot (they were my first cloud and personal choice), in an academic setting, we should train people in technology in a vendor-agnostic manner (even if AWS is participating in the teaching).

How do these ideas work using other clouds?

I will be coming back for more! Exciting stuff. I can't get enough of it.

Very nice course, good instructors that explain clearly all the technical devcelopments around LLM's. I did many courses developed by deepleaning.ai, but this one is certainly much better, than other courses not given by Andrew Ng. The labs are alo good, but perhaps it would be better that the student has to program a few lines of code. Thet is a little bit too easy now.

The course is a great tour for me toward the generative AI area with comprehensive labs that mention the representative papers, necessary techniques, AI project frameworks, and some tools and libraries. This experience gives me more confidence to explore higher levels in the rapidly developing direction of LLMs, especially after finishing the NLP specialization course.

This is a good course to take after the deep learning specialization series. It builds on top of the Transformer that was introduced in the Sequence Models. The labs take you through the workings of LLM: how to tune it, how to detect bias and how to leverage LLMs with external applications. Thank you to the instructors for very thorough explanations.