50.040 Natural Language Processing

Fall 2026 (Term 7) | Singapore University of Technology and Design (SUTD)

Past offering: Fall 2025

Announcements

Announcements will be made on the eDimension platform and by email.

Teaching Team

Instructors:

Teaching Assistants:

  • Luo Renjie (renjie_luo@mymail.sutd.edu.sg)
  • Zhang Yiyang (yiyang_zhang@mymail.sutd.edu.sg)
  • Yuhao Wu (wu_yuhao@mymail.sutd.edu.sg)

Grading Policy

Note: more details regarding the grading policy will be discussed in the first lecture.

  • Attendance & Participation: 10% (including 3 in-class quick quizzes)
  • Assignments (Individual): 30% (10% each)
  • Mid-term: 30% (Nov 2, during lecture time)
  • Final (Group) Project: 30%

Class Information

Lectures: LT2

  • Monday: 1:00PM – 3:00PM
  • Tuesday: 12:00PM – 2:00PM
  • Note: No recording or streaming, please come!

Cohorts: Cohort Classroom 14 (2.507A, 2.507B)

  • CI01: Thursday 5:00PM – 6:00PM
  • CI02: Thursday 4:00PM – 5:00PM
  • CI03: Thursday 2:00PM – 3:00PM
  • Note: Cohorts are biweekly, check the schedule below

Course Schedule

Note: the schedule is tentative and subject to change!

Materials: Lecture slides and cohort materials can be found on the eDimension platform.

Week Date Topics Materials / Readings Cohorts Deadlines
1 Mon, 14 Sep Course Logistics & Overview - - -
Tue, 15 Sep Introduction to NLP -
2 Mon, 21 Sep Recap on ML / Neural Networks 1. Stanford CS231n notes on neural network basics and backpropagation Word2Vec Tutorial HW1 Release
Tue, 22 Sep Word Vectors 1. Efficient Estimation of Word Representations in Vector Space (original word2vec paper)
2. The Illustrated Word2vec
3 Mon, 28 Sep Word Vectors (cont.) 1. word2vec Parameter Learning Explained - HW1 Due
Tue, 29 Sep Language Models 1. N-gram Language Models
2. BPE tutorial by Hugging Face
4 Mon, 5 Oct RNN and Variants 1. The Unreasonable Effectiveness of Recurrent Neural Networks
2. Understanding LSTM Networks 		RNN & Seq2Seq Tutorial -
Tue, 6 Oct Seq2Seq 1. Sequence to Sequence (seq2seq) and Attention (with good visualizations)
5 Mon, 12 Oct Seq2Seq with Attention 1. Neural Machine Translation by Jointly Learning to Align and Translate - HW2 Release
Tue, 13 Oct Project & Practical Tips
Project Announce		 1. Practical Methodology (Deep Learning book chapter)
6 Mon, 19 Oct Transformers 1. Attention Is All You Need
2. The Illustrated Transformer 		Transformer Tutorial HW2 Due
Tue, 20 Oct Transformers (cont.) 1. The Annotated Transformer
7 26 Oct Recess Week
8 Mon, 2 Nov Mid-term - Mid-term Review & Discussion -
Tue, 3 Nov Project Proposal Presentation -
9 Mon, 9 Nov Deepavali (no lecture) - - HW3 Release
Tue, 10 Nov Pre-training 1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
10 Mon, 16 Nov Post-training (SFT, RLHF) 1. Aligning language models to follow instructions (InstructGPT)
2. Scaling Instruction-Finetuned Language Models (Flan-T5) 		LLM Tutorial HW3 Due
Tue, 17 Nov Adaptation (Prompting & Adapter) 1. Language Models are Few-Shot Learners
2. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
3. LoRA: Low-Rank Adaptation of Large Language Models
11 Mon, 23 Nov Evaluation - - -
Tue, 24 Nov TBA -
12 Mon, 30 Nov Agents - Project Q&A -
Tue, 1 Dec Agents (cont.) -
13 Mon, 7 Dec Final Project Presentations - -
Tue, 8 Dec Final Project Presentations