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学生对 IBM 提供的 Generative AI Language Modeling with Transformers 的评价和反馈

4.5

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146 个评分

课程概述

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!...

26 - Generative AI Language Modeling with Transformers 的 31 个评论（共 31 个）

创建者 329_SUDIP C

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Dec 2, 2024

Nice Course

创建者 Purva T

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Jul 26, 2024

good.

创建者 Pravinkumar B A

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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.

创建者 Francesco D G

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Dec 15, 2024

Maybe a little chaotics. Slides should be available.

创建者 David C

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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Some labs are outdated, the contents are rushed and the assessments are inadequate.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.