---
title: Computational Linguistics
description: This interdisciplinary field focuses on the computational modeling of natural language. Learners will understand how computers process, analyze, and generate human language, preparing them to work with technologies like machine translation and speech recognition.
category: social-sciences
subcategory: linguistics
difficulty: beginner, intermediate, advanced
url: /subject/computational-linguistics
---

# Computational Linguistics

This interdisciplinary field focuses on the computational modeling of natural language. Learners will understand how computers process, analyze, and generate human language, preparing them to work with technologies like machine translation and speech recognition.

## Available Resources

2 Books • 2 Courses • 3 Websites

## Websites

### 1. spaCy Universe

A curated directory of plugins, pipelines, books, courses and demos built around the spaCy NLP library. Browse it to find maintained extensions for tasks like coreference, entity linking or annotation, plus tutorials from the wider community.

**Difficulty:** Beginner | **Price:** Free

**Link:** https://spacy.io/universe/

**Tags:** spacy, nlp-tooling, python, open-source-libraries

### 2. aclweb.org

ACLweb.org is the official site of the Association for Computational Linguistics, the premier hub for the field. It offers information on ACL conferences, membership, and access to key publications and learning resources for researchers and students.

**Difficulty:** Intermediate | **Language:** English | **Price:** Free

**Link:** https://aclweb.org

**Tags:** websites, humanities-social-sciences, linguistics

### 3. nltk.org

NLTK.org is the official site for the Python Natural Language Toolkit (NLTK). It provides documentation, tutorials, API references, and NLP resources (including corpora and the NLTK Book) to learn and experiment with language processing in Python.

**Difficulty:** Intermediate | **Language:** English | **Price:** Free

**Link:** https://nltk.org

**Tags:** websites, humanities-social-sciences, linguistics

## Courses

### 1. NLP Course

Learn NLP with the Hugging Face team! This comprehensive course covers natural language processing fundamentals and practical applications.

**Difficulty:** Intermediate | **Price:** Free

**Link:** https://huggingface.co/learn/nlp-course/chapter1/1

**Tags:** transformers, hugging-face, fine-tuning, datasets, text-classification

### 2. CS224N: Natural Language Processing with Deep Learning

Learn cutting-edge Natural Language Processing with Deep Learning in Stanford's CS224N course by Christopher Manning.

**Difficulty:** Advanced | **Price:** Free

**Link:** https://web.stanford.edu/class/cs224n/

**Tags:** deep-learning, word-embeddings, transformers, stanford, neural-machine-translation

## Podcasts

### 1. NLP Highlights

**Author:** Allen Institute for Artificial Intelligence

**The podcast is currently on hiatus. For more active NLP content, check out the Holistic Intelligence Podcast linked below.**
Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.

**Difficulty:** Beginner | **Language:** en | **Price:** Free

**Link:** https://soundcloud.com/nlp-highlights

**Tags:** nlp-research, research-interviews, allennlp, machine-learning

### 2. Last Week in AI

**Author:** Andrey Kurenkov, Jeremie Harris

A weekly news podcast in which the hosts summarize and discuss the week's developments in AI research, products, business and policy. Regular listening keeps you current on new models, notable papers, industry deals and regulation, with commentary separating substance from hype.

**Difficulty:** Beginner | **Language:** en | **Price:** Free

**Link:** https://art19.com/shows/last-week-in-ai

**Tags:** ai-news, machine-learning, ai-industry, ai-policy

## Books

### 1. Speech and Language Processing

**Author:** Daniel Jurafsky, James H. Martin

Free draft third edition of the standard NLP textbook, covering n-gram and neural language models, word embeddings, transformers, sequence labeling, parsing, machine translation and speech recognition. Readers gain the theory needed to build and evaluate modern language-processing systems.

**Difficulty:** Intermediate | **Language:** English | **Price:** Free

**Link:** https://web.stanford.edu/~jurafsky/slp3/

**Tags:** nlp, computational-linguistics, language-models, transformers, speech-recognition

### 2. Foundations of Statistical Natural Language Processing

**Author:** Christopher D. Manning, Hinrich Schütze

The standard graduate text on corpus-based language processing, covering n-gram models, word sense disambiguation, probabilistic parsing, alignment and text categorization. Working through it gives you the statistical foundations that modern neural NLP methods were built on.

**Difficulty:** Intermediate | **Language:** English | **Price:** Paid

**Link:** https://www.amazon.com/dp/0262133601?tag=edmonddante07-20

**Tags:** books, humanities-social-sciences, linguistics

---

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