Back to Generative AI Language Modeling with Transformers
Learner Reviews & Feedback for Generative AI Language Modeling with Transformers by IBM
147 ratings
About the Course
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!
Top reviews
MA
Jan 17, 2025
Exceptional course and all the labs are industry related
AB
Dec 29, 2024
This course gives me a wide picture of what transformers can be.
Filter by:
26 - 31 of 31 Reviews for Generative AI Language Modeling with Transformers
By 329_SUDIP C
•Dec 2, 2024
Nice Course
By Purva T
•Jul 26, 2024
good.
By Pravinkumar B A
•Nov 5, 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.
By Francesco D G
•Dec 15, 2024
Maybe a little chaotics. Slides should be available.
By David C
•Jul 27, 2025
Some labs are outdated, the contents are rushed and the assessments are inadequate. Nevertheless, it provides a good-enough broad and general picture.
By raul v
•Nov 20, 2025
los archivos de python contenían errores de compatibilidad de librerías.