JR
Was waiting for a course like this for a long time. Very happy with it. Library installation on labs seems a bit slow

The Gen AI market is expected to grow 46% . yearly till 2030 (Source: Statista). Gen AI engineers are high in demand. This program gives aspiring data scientists, machine learning engineers, and AI developers essential skills in Gen AI, large language models (LLMs), and natural language processing (NLP) employers need. Gen AI engineers design systems that understand human language. They use LLMs and machine learning to build these systems. During this program, you will develop skills to build apps using frameworks and pre-trained foundation models such as BERT, GPT, and LLaMA. You’ll use the Hugging Face transformers library, PyTorch deep learning library, RAG and LangChain framework to develop and deploy LLM NLP-based apps. Plus, you’ll explore tokenization, data loaders, language and embedding models, transformer techniques, attention mechanisms, and prompt engineering. Through the series of short-courses in this specialization, you’ll also gain practical experience through hands-on labs and a project, which is great for interviews. This program is ideal for gaining job-ready skills that GenAI engineers, machine learning engineers, data scientists and AI developers require. Note, you need a working knowledge of Python, machine learning, and neural networks.. Exposure to PyTorch is helpful.

JR
Was waiting for a course like this for a long time. Very happy with it. Library installation on labs seems a bit slow
PG
The lab materials are very complicated could be made abstract using tensorflow.
RR
Once again, great content and not that great documentation (printable cheatsheets, no slides, etc). Documentation is essential to review a course content in the future. Alas!
AE
The course is good but lacks depth on complex subjects.
SG
An excellent course with a wealth of high-quality material, featuring highly informative lessons such as DPO and PPO.
AM
The robotic voice of the reader made the experience a little fake, but the content was interesting
HA
Simply great! Learnt a lot and also enjoyed the labs!
AS
gives a clear overview on genai - basics specifically tokenization, & data loader concepts
SG
Super course,.. labs are too good to learn and challenging too.
PA
Excellent course to understand about AI/ML/GenAI. The videos are not very detailed and just the right amount to skim through the details.
RK
The labs all too often failed on environment issues - packages, version alignment, etc. This should be seamless in your controlled environment.
AV
Very Informative – Covers advanced fine-tuning techniques in a clear and structured way
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This is an extremely un-educational course and a hugely frustrating experience from a seasoned learner's perspective. It is fundamentally a voice going through whatever info appears on a series of slide stacks just like a robot would. There is no effort whatsoever in trying to make you understand anything and no actual time to do it while you hear the voice running through the text. The only practical way to acquire the knowledge contained in the slides is to stop every 30 seconds, read, look up somewhere else (google, forums...) to actually consolidate the knowledge, and then click the play button again. I am a proficient and quick learner and have a good background on neural networks and gen-ai use and programming and I was completely incapable of following the explanations given in this course after the first 5 minutes: boring, robotic, ineffectual, and very counter-productive. This has been a very frustrating experience from a learner's perspective and my advice would be to take this course out and rethink it from scratch, as it certainly does not serve its purpose at all. I left one star because the knowledge is actually there in the slides. The information is contained in the slides, it is simply never actually conveyed to the audience by the reading robotic entity in charge.
I think this course needs a couple of hours more with more detail on the architecture and coding. I did get useful information from Coach and ChatGPT though, but it might be more precise if its in the course.
As someone who recently took up this course, I must say it has been an incredible journey into the world of generative AI! The course covers a perfect blend of theoretical and hands-on learning, making complex concepts like LLM architectures and generative models feel much more approachable. What stood out to me was how clearly the differences between various generative models were explained, including their unique training approaches. The module on building a chatbot using the Hugging Face transformers library was especially exciting. It’s amazing how we got to implement something so practical and see it come to life! The course didn’t just stop at theory; it also guided us through implementing a data loader with PyTorch's DataLoader class, which gave a solid understanding of real-world application. Overall, this course is perfect for anyone wanting to dive deep into generative AI, particularly in the field of NLP. Highly recommend it!
Extremely comprehensive course, goes in great detail about all the different Generative AI architectures and models, and the different tokenization methods used that enable us to have NLP, it explains them thoroughly, and then provides you with a lab so that you get to experiment and apply this info in a practical setting. Personally I respect courses that truly give you fundamental information, and not just narrate general information, through experience I noticed IBM courses out of all course providers care about making their course as useful as possible, many other course creators spend more time setting up cameras in professional studios with flashy editing, to make their course look good, rather than being informative. IBM in the other hand is all about knowledge, and nothing more.
I recently completed the course "Generative AI and LLMs: Architecture and Data Preparation," and it was an outstanding experience! The content was well-structured and provided deep insights into the architecture and data handling essential for working with large language models. The instructors were knowledgeable and engaging, making complex concepts easy to grasp. I highly recommend this course to anyone looking to enhance their understanding of generative AI!
Was waiting for a course like this for a long time. Very happy with it. Library installation on labs seems a bit slow
Excelente curso, muy completo, la teoría esta muy bien explicada, ademas lo mejor son las sesiones de prácticas con los notebooks, realmente lo recomiendo.
De fácil compreensão e com um aprendizado profundo, é uma excelente oportunidade para aprender sobre o assunto do momento.
I am pretty much new to NLP data preparation. However this course made me comfortable with Date preparation activities.
Excellent and very comprehensive course. I learnt a lot from the excellent material that was provided.
I love the structure and the content in this course. I can't wait applying the skills I have acquired!
Easy to follow course with good clarification of complex concepts. Thanks to IBM and to course team.
A clear introduction on GAI and LLM, with some exercises to get familiar with the implementation
this course is great but I need the digital badges to be added to Credly, how can I do that?
gives a clear overview on genai - basics specifically tokenization, & data loader concepts
It was very informative and I enjoyed the journey I learned the patterns from the deep.
excelente curso , describe acertadamente los diferentes modelos de IA y tokenizacion
I love this course, it is what I was looking for a long time, Thank you IBM team !
I have learned so much from this course and I can't wait to start my AI career.
this course was very beneficial with detail material and easy to understand