This IBM course will equip you with the skills to implement, train, and evaluate generative AI models for natural language processing (NLP) using PyTorch. You will explore core NLP tasks, such as document classification, language modeling, and language translation, and gain a foundation in building small and large language models.
You will learn how to convert words into features using one-hot encoding, bag-of-words, embeddings, and embedding bags, as well as how Word2Vec models represent semantic relationships in text. The course covers training and optimizing neural networks for document categorization, developing statistical and neural N-Gram models, and building sequence-to-sequence models using encoder–decoder architectures. You will also learn to evaluate generated text using metrics such as BLEU. The hands-on labs provide practical experience with tasks such as classifying documents using PyTorch, generating text with language models, and integrating pretrained embeddings like Word2Vec. You will also implement sequence-to-sequence models to perform tasks such as language translation. Enroll today to build in-demand NLP skills and start creating intelligent language applications with PyTorch.
TM
the material is topnotch but the delivery is a bit fast I would rather it was slower
GO
I have enjoyed myself in this course. I can't wait to apply the skills I have learned in this class. Thank you the fantastic Team.
SG
Super course,.. labs are too good to learn and challenging too.
PG
The lab materials are very complicated could be made abstract using tensorflow.
AB
Got the base understanding of N-gram, skip-gram, RNN, and other NLP techniques
RR
AI Foundational and LLMs is learning career growth.
VP
Overall good course but the videos could use better pacing
JG
Great course to get involved with NLP and GenAI, It has the good balance between necessary explanations and lab examples. It would have been nice to have access to GPUs in the labs.
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This is an extremely un-educational course and a hugely frustrating experience. It is fundamentally a voice going through whatever appears on a series of slide stacks just like a robot would. There is no effort 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.
the lab code is buggy. You face issues with almost every cell. Some core concepts on which entire module relies itself are outdated or are deprecated. For eg torchtext was deprecated in 2023. What is the point of teaching it in 2024. Extremely disappointed with IBM...
I think the videos were bad for a number of reasons: - there was an odd amount of explanation of what neural networks are. you should assume by this point we know what a neural network is. - the videos were very bad at explaining concepts. I think longer videos that explain more clearly what the object are would serve this course well - the explanation of what an RNN in was awful. - i thought the explanation of embeddings layers was awful. - in the word2vec lab, the visualization in the plane in the lab doesn't match up with your explanation underneath at all. - you hardly explain the mathematics behind everything (fine, this is not a math class) but then blow through the coding implementation. please choose one or the other and explain more. To reiterate, I think these topics are far too subtle to compress into 2 minute video, and you should provide references for further reading. This was far and away the worst of the AI engineering stream.
Uselessly filled with complex mathematical notation, less focused on explaining the concept in an easy to understand way. First few courses of the certificate was amazing, the next few by this guy, abysmal.
Badly curated, videos don't explain much. Jupyter sessions are interesting code snippets, but again the knowledge is not transmitted well.
3* because of the videos and materials. if it would be only about labs it would be 4*. Video materials could be much more than slides and AI generated speech. Even with prior theoretical knowledge, videos were confusing to me. It seemed like there were some explanations missing, or glue between the slides and subtopics. And this was especially present in the Module 2. I strongly suggest to either go through deep learning and/or NLP courses by deeplearning.ai or to try to find their or someone else's videos on YouTube. In that context, course could have been complemented with more materials for theoretical concepts. IBM courses so far are lacking good theoretical base and explanations. Labs were good and can be even better if for module 2 connection between encoder and decoder was visually better explained (e.g. more gifs).
I have enjoyed myself in this course. I can't wait to apply the skills I have learned in this class. Thank you the fantastic Team.
Got the base understanding of N-gram, skip-gram, RNN, and other NLP techniques
Super course,.. labs are too good to learn and challenging too.
Overall good course but the videos could use better pacing
Very clear introduction of the NLP with hands-on exercises
AI Foundational and LLMs is learning career growth.
Short and precise course with good explanation.
it's a great course with awesome subjects.
Great learning...amazing course.
Excellent content
Very informative
Very informative
excellent course
Great Course