Bottom line: NLP skills now combine classic text processing, embeddings, transformers, retrieval, and LLM application design.

Natural Language Processing Course

Learn NLP with text processing, embeddings, transformers, classification, summarization, RAG, evaluation, and LLM application patterns.

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NLP Topics

Important topics include tokenization, text cleaning, embeddings, classification, sequence models, transformers, summarization, search, and evaluation.

Modern NLP

Modern NLP includes LLM prompting, retrieval, reranking, instruction following, structured extraction, and safety-aware response design.

Projects

Learners can build classifiers, summarizers, chat assistants, document search tools, extraction workflows, and support copilots.

Frequently Asked Questions

What is NLP in AI?

Natural language processing is the AI field focused on helping software understand, search, transform, and generate human language.

Is NLP still useful with LLMs?

Yes. LLMs make NLP more powerful, but developers still need text processing, retrieval, evaluation, and application design skills.