Course
LING 529: HLT I
Human Language Technology I: programming, tools, and foundational language technology practice.
Selected materials that combine conceptual explanation with executable or visual examples.
Course
Human Language Technology I: programming, tools, and foundational language technology practice.
Course
A short Python refresher with embedded Etude practice for students preparing for Human Language Technology I.
Course
Methods and ethics in linguistic research, with language technology oriented toward data sovereignty and community-defined needs.
Human Language Technology I: programming, tools, and foundational language technology practice.
A short Python refresher with embedded Etude practice for students preparing for Human Language Technology I.
Methods and ethics in linguistic research, with language technology oriented toward data sovereignty and community-defined needs.
Statistical NLP, text representation, classification, sequence tagging, parsing, and applied machine learning foundations.
Advanced NLP with deep learning, neural networks, transformers, LLMs, and practical model-development workflows.
Professional practice for HLT students, including career planning, profiles, interviews, and portfolio development.
General Python references and practice materials for students getting ready to work with language data.
Selected technical references and student-facing guides. The full tutorial index includes 32 public lessons.
All tutorialsIn this lesson, we'll learn some of the key concepts behind clustering.
In this lesson, we'll learn about distance and similarity metrics.
This lesson introduces you to the basics of Docker.
In this lesson, you'll learn how to use to represent words and documents with vectors of features.
This tutorial introduces the course workflow for using Forgejo repositories created through Class Maestro.
This lesson introduces you to the basics of the Git version control system.
This tutorial introduces you to using GitHub.
This lesson introduces tokenization as the step where language models turn written text into token IDs. It includes a short concrete example using the tokenizer associated with gpt-oss-20b, without loading the model weights.
Short-form teaching materials for specific events and training contexts.
CoLang workshop materials introducing relational database design for language workers and language technology projects.
Welcome to Intro to NLP: Representing words and documents as vectors. This is an introductory-level NLP tutorial for Resbaz 2022!
Orientation notes, program resources, and advice for Human Language Technology students.
Program hubFirst, I would say not to worry. Many students enter the program with little to no background in programming or advanced math. We're dealing with an onion here. The HLT program will guide you through what you need to understand things at a high level and then grow...
Many students and instructors find this textbook very easy to read:
Welcome to the University of Arizona's online MS program in Human Language Technology. We're thrilled to have you join us!