返回到 Generative AI Language Modeling with Transformers
IBM

Generative AI Language Modeling with Transformers

This course provides a practical introduction to using transformer-based models for natural language processing (NLP) applications. You will learn to build and train models for text classification using encoder-based architectures like Bidirectional Encoder Representations from Transformers (BERT), and explore core concepts such as positional encoding, word embeddings, and attention mechanisms. The course covers multi-head attention, self-attention, and causal language modeling with GPT for tasks like text generation and translation. You will gain hands-on experience implementing transformer models in PyTorch, including pretraining strategies such as masked language modeling (MLM) and next sentence prediction (NSP). Through guided labs, you’ll apply encoder and decoder models to real-world scenarios. This course is designed for learners interested in generative AI engineering and requires prior knowledge of Python, PyTorch, and machine learning. Enroll now to build your skills in NLP with transformers!

状态:Text Mining
状态:Generative AI
中级课程小时

精选评论

AB

5.0评论日期:Dec 29, 2024

This course gives me a wide picture of what transformers can be.

MA

5.0评论日期:Jan 17, 2025

Exceptional course and all the labs are industry related

PA

4.0评论日期:Nov 4, 2025

Excellent course to understand about AI/ML/GenAI. The videos are not very detailed and just the right amount to skim through the details.

VB

4.0评论日期:Nov 16, 2024

need assistance from humans, which seems lacking though a coach can give guidance but not to the extent of human touch.

RR

4.0评论日期:Oct 10, 2024

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!

RR

5.0评论日期:Sep 1, 2025

I loved this course. It is very informative and has a lot of examples. It will take some time to master all this information.

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