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Curriculum/LLM Research and NLP/What LLM and NLP Research Is
20 minIntermediate

What LLM and NLP Research Is

After this lesson, you will be able to: Understand what NLP/LLM research is, how it differs from using AI as a practitioner, and how this track takes you toward submitting work to a venue like the ACL Student Research Workshop.

This is a parent track with four sub-tracks: Transformers and NLP Foundations, Fine-Tuning and Adaptation, Evaluation and Experimental Rigor, and Research Practice and Publishing at ACL SRW. It assumes you can program in Python and have seen a neural network before, then takes you from the transformer architecture up to drafting and submitting a short research paper.

This is a free introductory lesson. No purchase required.

Using AI vs researching AI

The Artificial Intelligence track on LastWrite teaches you to build with LLMs: call APIs, prompt well, ship features. This track is different. It teaches you to study LLMs as objects of research: how the architecture works at the level of equations, how to train and adapt models yourself, how to measure them rigorously, and how to write up a finding so other researchers can trust and build on it. The end goal is a contribution someone could present at a workshop, not a product.

What the ACL Student Research Workshop is

The ACL (Association for Computational Linguistics) runs the top venues in NLP: ACL, EMNLP, NAACL, EACL. Each hosts a Student Research Workshop (SRW), a track designed specifically for students to present early-stage or completed work and get feedback from a senior mentor. The SRW is the standard on-ramp into the research community: shorter papers, a mentorship program, and a lower bar than the main conference, but the same peer-review process. This track is built to get you to a credible SRW submission.

How the four sub-tracks fit together

Take Foundations first: it builds the transformer from tokenization and attention up, so nothing later is a black box. Fine-Tuning teaches you to adapt models with LoRA on real hardware budgets. Evaluation teaches the rigor reviewers demand, which is where most rejected papers actually fail. Publishing teaches the research craft: reading papers, reproducing one, writing in the ACL format, and navigating ACL Rolling Review and the SRW. Each sub-track ends with a portfolio project and a job/research-readiness lesson.

ℹ️ What you need going in

Comfort with Python (the Programming Languages > Python sub-track is enough), and the conceptual AI background from the Artificial Intelligence track (what a neural network and an LLM are). You do not need a GPU to start: the hands-on lessons use free Colab or Kaggle notebooks and small models. You do need patience for math: this track shows the equations, not just the metaphors.

Tools & Resources

ACL Student Research Workshop (overview)
ACL Anthology (every NLP paper, free)
Hugging Face course (free)
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