Natural Language Processing

(CSCI-SHU 376)

Spring 2026 | New York University Shanghai

Hua Shen

Instructor

Hua Shen

Time Tue/Thu 11:15 AM - 12:30 PM
Location N401
Welcome! 🤗
Natural language processing (NLP), a form of artificial intelligence (AI) that gives computers the ability to read, understand and interpret human languages, is one of the most important technologies that have made significant progress recently. NLP has been applied to many areas such as machine translation, question answering, summarization, dialogue etc. The course will introduce students to the basics of NLP, including standard frameworks as well as algorithms and techniques to solve NLP problems, including recent deep learning approaches.

Overview
Office Hour
Hua Shen: 2:30 PM - 4:00 PM, Friday (or by appointment);
Office: S749; Zoom: https://nyu.zoom.us/my/hua.shen (Passcode: enQb9h)
Prerequisite:
Required: Machine Learning, Calculus, Probability and Statistics;
Desirable/Helpful: Linear Algebra, Data Structures, Pytorch
Class Schedule
See NYU Shanghai's Course Syllabus for the tentative schedule, which is subject to change.
Date Theme Topics Reading Materials
1
Jan 20 (Tue) Overview
Overview: NLP Landscape
Lecture 1
1
Jan 22 (Thu) Overview
Course Objectives & Teaming Up
🎓 Project Proposal Start Team Sheet
2
Jan 27 (Tue) Theme 1: Statistical and Feature-Based NLP
N-Gram LMs
Lecture 2
2
Jan 29 (Thu) Theme 1: Statistical and Feature-Based NLP
Text Classification & Log-Linear Models
🎓 Quiz 1
Lecture 3
3
Feb 3 (Tue) Theme 2: Neural NLP
Word Embeddings, Pytorch Foundation
🎓 Quiz 2 🎓 HW1 Out
3
Feb 5 (Thu) Theme 2: Neural NLP
Sequance Modeling & Neural Networks
🎓 Project Proposal Due
4
Feb 10 (Tue) Theme 2: Neural NLP
RNN & LSTM
4
Feb 12 (Thu) Theme 2: Neural NLP
Sequence to Sequence Models
🎓 Quiz 3
5
Feb 17 - Feb 19
💃🏻 Spring Festival Holiday - No Class
6
Feb 24 (Tue)
NO CLASS, Meet Hua about Project Progress
🎓 HW1 Due
6
Feb 26 (Thu) Theme 3: Transformers & Pretraining
Transformers
🎓 HW2 Out
7
Mar 3 (Tue) Theme 3: Transformers & Pretraining
Contextualized representations and LM-pretraining
🎓 Quiz 4
7
Mar 5 (Thu) Theme 4: Foundation Models / LLMs
LLM Pretraining and Instruction Finetuning
slides
8
Mar 10 (Tue) Theme 4: Foundation Models / LLMs
LLM in-context Learning and RLHF
8
Mar 12 (Thu) Theme 4: Foundation Models / LLMs
LLM Decoding
🎓 Quiz 5
9
Mar 17 (Tue) MIDTERM 🎓 Midterm Exam 🎓 HW2 Due, HW3 Out
9
Mar 19 (Thu) Theme 5: Open Research Directions of LLMs
Retrieval-augmented LLM
10
Mar 24 (Tue) Theme 5: Open Research Directions of LLMs
LLM Reasoning
10
Mar 26 (Thu) Theme 5: Open Research Directions of LLMs
Value Alignment of LLM
11
Mar 31 (Tue)
🎓 Mid-Project Presentation I
11
Apr 2 (Thu)
🎓 Mid-Project Presentation II
🎓 HW3 Due
12
Apr 7 (Tue)
💃🏻 Qingming Festival Holiday - No Class
12
Apr 9 (Thu)
💃🏻 Qingming Festival Holiday - No Class
13
Apr 14 (Tue)
CHI Conference - No Class
13
Apr 16 (Thu)
CHI Conference - No Class
14
Apr 21 (Tue) Theme 6: Agentic LLMs
LLM Agents
14
Apr 23 (Thu) Theme 6: Agentic LLMs
Multi-Agent Systems
15
Apr 28 (Tue) Theme 7: Speech Processing
Speech Features and Automatic Speech Recognition (ASR)
15
Apr 30 (Thu) Theme 7: Speech Processing
Text-to-Speech
16
May 5 (Tue)
NO CLASS, Meet Hua about Project Progress
16
May 7 (Thu)
🎓 Final-Project Presentation I
17
May 12 (Tue)
🎓 Final-Project Presentation II
17
May 14 (Thu)
🎓 Final-Project Presentation III
🎓 Final Project Due