This schedule is tentative and subject to change.
| Week | Date | Topic | HW Assigned | HW Due |
|---|---|---|---|---|
| 1 | Jan 14 | Intro: NLP Landscape and History, Course Objectives | ||
| Jan 16 | Intro: Representation in NLP | |||
| 2 | Jan 21 | Designing, Evaluating, and Incrementally Improving NLP Systems | ||
| Jan 23 | Probability Theory and Language Modeling | |||
| 3 | Jan 28 | Naive Bayes and Document Classification | ||
| Jan 30 | Logistic Regression | |||
| 4 | Feb 4 | Softmax Regression | HW1: Language ID | |
| Feb 6 | Feed-Forward Neural Networks | |||
| 5 | Feb 11 | Word Embeddings | Distributional Semantics | |
| Feb 13 | Modeling Sequences: RNNs and NER | |||
| 6 | Feb 18 | Encoder-Decoder, Beam Search | HW2: Language Modeling | HW1 |
| Feb 20 | Self-Attention and Transformers | |||
| 7 | Feb 25 | Recitation: Pytorch | ||
| Feb 27 | Midterm Exam | |||
| - | Mar 4 | Spring Break | ||
| Mar 6 | Spring Break | |||
| 8 | Mar 11 | LLMs I: Pretraining, Encoder-only (BERT), Finetuning | ||
| Mar 13 | LLMs II: Encoder-Decoder (T5) and Decoder-Only (GPT), ICL | HW3: Clickbait Detection | HW2 | |
| 9 | Mar 18 | LLMs III: RLHF, DPO, Guardrails | ||
| Mar 20 | Ethics and NLP | |||
| 10 | Mar 25 | Syntax and Parsing | HW 4: Named Entity Recognition | HW3 |
| Mar 27 | Semantics and Reasoning over Knowledge Representations | |||
| 11 | Apr 1 | Natural Language Inference | ||
| Apr 3 | Machine Translation | |||
| 12 | Apr 8 | Multilingual NLP | ||
| Apr 10 | Carnival | |||
| 13 | Apr 15 | Information Extraction | Coreference | |
| Apr 17 | History of QA (including NER, IR, scoring) | |||
| 14 | Apr 22 | Modern QA (reader/retriever, LLM, prompting, RAG, etc.) | ||
| Apr 24 | Final Review |
For more detailed information about each lecture, please check the corresponding links in the schedule above or visit the Resources page.
