Courses and slide resources for learning about Large Language Models (LLMs)

Here’s a list of standard, high-quality courses and slide resources for learning about Large Language Models (LLMs), organized by depth and source type:

A. Courses

1. Stanford CS224N – Natural Language Processing with Deep Learning

Institution: Stanford University

Lecturer: Christopher Manning

URL: https://web.stanford.edu/class/cs224n/

Content:

Word vectors, embeddings

RNNs, LSTMs, GRUs

Transformers

BERT and GPT

Attention, self-attention

Sequence-to-sequence models

Machine translation

Slides + Video Lectures Available

1. DeepLearning.AI NLP Specialization (Coursera)

Platform: Coursera

Instructor: Younes Bensouda Mourri, Łukasz Kaiser

URL: https://www.coursera.org/specializations/natural-language-processing

Content:

Text classification, language modeling

Sequence models

Attention

Transformers

BERT-style pretraining

1. Hugging Face Course (Free)

Platform: Hugging Face

URL: https://huggingface.co/learn/nlp-course/

Content:

Transformers architecture

Tokenization and pipelines

Using pretrained models

Fine-tuning with real code

Deployment and scaling

1. MIT 6.S191 – Deep Learning

URL: https://introtodeeplearning.com/

Includes: Transformers, sequence modeling

Slides + Python Notebooks + Lectures

1. Fast.ai NLP

Platform: Fast.ai

URL: https://course.fast.ai/

Focus: Practical and applied deep learning with code

Includes: Text classification, transfer learning, ULMFiT

B. Slides & Lecture Notes

1. Lilian Weng (OpenAI) – Transformer Primer

URL: https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html

Detailed breakdown of attention mechanisms and Transformers.

1. Jay Alammar Visual Guides

URL:

Transformers: http://jalammar.github.io/illustrated-transformer/

BERT: http://jalammar.github.io/illustrated-bert/

GPT-2: http://jalammar.github.io/illustrated-gpt2/

Uses diagrams and simplified flowcharts.

1. Berkeley NLP Lecture Slides

Course: CS 288 (Neural NLP)

URL: https://people.eecs.berkeley.edu/~pliang/courses/cs288-fa21/
https://people.eecs.berkeley.edu/~klein/cs288/fa14/slides/

Includes slides, code, and problem sets.

Others: slides

LM-class | an educational resource for contemporary language modeling
https://lm-class.org/

Large Language Models | ÚFAL
https://ufal.mff.cuni.cz/courses/npfl140

Large Language Models, Spring 2024 | Rycolab
https://rycolab.io/classes/llm-s24/

Large Language Model Agents
https://llmagents-learning.org/f24