Standard syllabus
Natural language processing · Graduate · CS / Programming
Topics
Classical NLP
- Tokenization, morphology, and n-gram language models
- Part-of-speech tagging and HMMs (intro)
- Context-free parsing and dependency parsing (intro)
- Word embeddings: Word2Vec, GloVe
- Information retrieval and TF-IDF baselines
Neural NLP
- Recurrent networks for sequence labeling
- Attention mechanisms and Transformer architecture
- Pretrained language models (BERT, GPT family survey)
- Fine-tuning vs prompting paradigms
- Evaluation metrics: perplexity, BLEU, ROUGE (intro)
Pricing
Graduate-level rates are set on consultation. See the pricing page for K–12 and undergraduate rates.