Detailed Course Schedule

This schedule is tentative! If we fall behind, topics and assignments may be moved to later weeks in the semester.

Each topic links to a PDF with slides, once available.

	Date	Topic	Assigned	Due
Week 1
Tu	2/13	Syllabus Overview, Tokens, Corpora	Background Survey
Tokenization, Corpora (J&M 2.0, 2.2-2.3) In-Class Activitites NLP Tasks and Systems Rule-Based Tokenization GPT Tokenization
Th	2/15	Regular Expressions, Reading Papers	HW 1	Background Survey
Regular Expressions (J&M 2.1) Srinivasan Keshav (2007), How to Read a Paper In-Class Activitites Regular Expressions
Week 2
Tu	2/20	N-Gram Language Models		Paper Selection (DUE BY 11:30AM)
N-Gram Language Models (J&M 3.0-3.6.2) In-Class Activitites N-Gram Language Modeling Code
Th	2/22	Naive Bayes, Classifier Evaluation	HW 2	HW 1
Naive Bayes and Sentiment Classification (J&M 4.0-4.3, 4.5-4.8, 4.10) In-Class Activitites Worksheet Worksheet Solution
Week 3
Tu	2/27	Part of Speech Tagging with Hidden Markov Models
Sequence Labeling for Parts of Speech (J&M 8.0-8.2, 8.4) In-Class Activitites Worksheet Worksheet Solution
Th	2/29	Logistic Regression	HW 3	HW 2
Logistic Regression (J&M 5.0-5.6.3) In-Class Activitites Worksheet Worksheet Solution Logistic Regression Code (Colab)
Week 4
Tu	3/5	Vector Semantics
Vector Semantics (J&M 6.0-6.7) In-Class Activitites Worksheet Worksheet Solution Logistic Regression and Vector Semantics Example Code (Colab)
Th	3/7	Word2Vec	HW 4	HW 3
Word2Vec (J&M 6.8-6.12) In-Class Activitites Semantic Change Data Collection Embedding Experimentation
Week 5
Tu	3/12	Neural Networks for Text Classification
Neural Networks (J&M 7.0-7.4, 7.5 is optional) In-Class Activitites Worksheet Worksheet Solution XOR Code
Th	3/14	Neural Networks for Text Classification (II)		HW 4
In-Class Activitites Emotion Classification Code
Week 6
Tu	3/26	BERT for Text Classification
Jay Alammer (2018), The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) In-Class Activitites Extracting Contextual Embeddings from BERT Ada Cluster Guide
Th	3/28	BERT for Text Classification (II)	HW 5	Partner Interest Form (DEADLINE EXTENDED to Monday, 11:59PM)
Jay Alammer (2017), The Illustrated Transformer (Read until the start of the "The Decoder Side" section) In-Class Activitites Mid-Semester Feedback The BERT Encoder
Week 7
Tu	4/2	Neural Language Modeling		Partner Interest Form (DUE AT NOON)
Neural Language Modeling (J&M 7.6-7.7) Transformer LMs and Sampling from LLMs (J&M 10.6-10.8) In-Class Activitites Worksheet Worksheet Solution
Th	4/4	Machine Translation	HW 6	HW 5
Machine Translation and Evaluation (J&M 13.0-13.8 (focus on 13.4, 13.6)) In-Class Activitites Beam Search Colab Notebook Worksheet Worksheet Solution
Week 8
Tu	4/9	Ethics in NLP: Data
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford (2021), Datasheets for Datasets J. Edward Moreno (2023), Boom in A.I. Prompts a Test of Copyright Law (make sure you've activated your free New York Times subscription through Middlebury!) In-Class Activitites Textual entailment annotation activity
Th	4/11	Ethics in NLP: Models	HW 7	HW 6 Project Proposal
Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru (2019), Model Cards for Model Reporting Rachael Tatman (2020), What I Won't Build (talk recording) In-Class Activitites Research using your data survey Ethics of NLP Models Discussion (google sheets)
Week 9
Tu	4/16	Language Understanding
Emily M. Bender, Alexander Koller (2020), Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (there is also an audio paper available - feel free to listen if you want a break from reading!) In-Class Activitites Language Understanding Survey
Th	4/18	Literature Reviews (Section A), Guest Lecture from Julia Kroll (Section B)		HW 7
Voicing concerns: The future of AI voice replacement (Podcast - Section B) In-Class Activitites Presentation Information Finding Papers Using Overleaf
Week 10
Tu	4/23	Guest Lecture from Julia Kroll (Section A), Literature Reviews (Section B)
Voicing concerns: The future of AI voice replacement (Podcast - Section A) In-Class Activitites Presentation Information Finding Papers Using Overleaf
Th	4/25	NER, Common Project Challenges and Solutions		Project Check-In 1
In-Class Activitites Sticker Voting Project Challenges and Solutions (Colab) Named Entity Recognition (Colab)
Week 11
Tu	4/30	Unsupervised Learning in NLP
In-Class Activitites Exploring Topic Models
Th	5/2	Preparing Project Presentations		Project Check-In 2
In-Class Activitites Project Posters Project Demos with Gradio
Week 12
Tu	5/7	NLP in the Age of LLMs
Th	5/9	Project Presentations		Draft Report and Code (optional but strongly recommended)