Natural Language Processing

Natural language processing turns unstructured text into something a system can act on. Courses progress from tokenisation, lemmatisation and classical approaches such as TF-IDF and topic modelling, through word and sentence embeddings, to transformer architectures and the Hugging Face ecosystem. Applications covered include text classification, sentiment analysis, named entity recognition, summarisation, semantic search and machine translation. Several courses address non-English and low-resource languages, which matters if you work with Vietnamese text. Complementary to the Generative AI section: this teaches the language processing groundwork that LLM applications sit on top of.