Natural Language Processing Specialization

Four courses move from sentiment analysis and word embeddings through LSTM sequence models to the transformer architecture behind BERT and GPT — and the transformer module is taught by Łukasz Kaiser, a co-author of the original Attention Is All You Need paper. It is one of the better-structured NLP routes.

What it does not do is serve beginners — it is advanced and expects solid Python, ML and some maths — and it will not suit you if you only want to use language models rather than understand them; an applied LLM course fits better instead. The certificate needs a subscription; the free audit covers the learning, and it is kept updated though the field moves fast.","Implement attention and transformer models from the ground up"}

This four-course specialization covers NLP from classical ML through modern deep learning: sentiment analysis, word embeddings, sequence models with LSTMs, and finally the transformer architecture that underpins BERT and GPT.