A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era

Angel Daza

A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era

Correct Metadata for

Use this form to create a GitHub issue with structured data describing the correction. You will need a GitHub account. Once you create that issue, the correction will be reviewed by a staff member.

⚠️ Mobile Users: Submitting this form to create a new issue will only work with github.com, not the GitHub Mobile app.

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>. You may use <b>...</b> for bold, <i>...</i> for italic, and <url>...</url> for URLs.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

With the advent of Large Language Models (LLMs) researchers outside the Natural Language Processing (NLP) field are interested in learning how to process textual data for their own domain research goals. They are particularly motivated to start experimenting directly with LLMs, implicitly neglecting the large amount of accumulated knowledge that NLP has to offer them. In this text, we briefly share our new lesson materials that aim to show aspiring practitioners the strong connection between NLP fundamentals and LLMs, in the form of a two-day workshop. Our training material is mainly aimed at graduate students outside the NLP sphere who have basic technical knowledge and wish to start working with text, is fully open source and available online.

Anthology ID:: 2026.teachingnlp-1.7
Volume:: Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026)
Month:: March
Year:: 2026
Address:: Rabat, Morocco
Editors:: Matthias Aßenmacher, Laura Biester, Claudia Borg, György Kovács, Margot Mieskes, Sofia Serrano
Venues:: TeachingNLP | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 37–40
Language:
URL:: https://aclanthology.org/2026.teachingnlp-1.7/
DOI:
Bibkey:
Cite (ACL):: Angel Daza. 2026. A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era. In Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026), pages 37–40, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):: A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era (Daza, TeachingNLP 2026)
Copy Citation:
PDF:: https://aclanthology.org/2026.teachingnlp-1.7.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{daza-2026-hands-approach,
    title = "A Hands-on Approach to {NLP} Fundamentals for External Domain Experts in the {LLM} Era",
    author = "Daza, Angel",
    editor = {A{\ss}enmacher, Matthias  and
      Biester, Laura  and
      Borg, Claudia  and
      Kov{\'a}cs, Gy{\"o}rgy  and
      Mieskes, Margot  and
      Serrano, Sofia},
    booktitle = "Proceedings of the Seventh Workshop on Teaching Natural Language Processing ({T}each{NLP} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.teachingnlp-1.7/",
    pages = "37--40",
    ISBN = "979-8-89176-375-3",
    abstract = "With the advent of Large Language Models (LLMs) researchers outside the Natural Language Processing (NLP) field are interested in learning how to process textual data for their own domain research goals. They are particularly motivated to start experimenting directly with LLMs, implicitly neglecting the large amount of accumulated knowledge that NLP has to offer them. In this text, we briefly share our new lesson materials that aim to show aspiring practitioners the strong connection between NLP fundamentals and LLMs, in the form of a two-day workshop. Our training material is mainly aimed at graduate students outside the NLP sphere who have basic technical knowledge and wish to start working with text, is fully open source and available online."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="daza-2026-hands-approach">
    <titleInfo>
        <title>A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Angel</namePart>
        <namePart type="family">Daza</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-03</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Matthias</namePart>
            <namePart type="family">Aßenmacher</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Laura</namePart>
            <namePart type="family">Biester</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Claudia</namePart>
            <namePart type="family">Borg</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">György</namePart>
            <namePart type="family">Kovács</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Margot</namePart>
            <namePart type="family">Mieskes</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sofia</namePart>
            <namePart type="family">Serrano</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Rabat, Morocco</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-375-3</identifier>
    </relatedItem>
    <abstract>With the advent of Large Language Models (LLMs) researchers outside the Natural Language Processing (NLP) field are interested in learning how to process textual data for their own domain research goals. They are particularly motivated to start experimenting directly with LLMs, implicitly neglecting the large amount of accumulated knowledge that NLP has to offer them. In this text, we briefly share our new lesson materials that aim to show aspiring practitioners the strong connection between NLP fundamentals and LLMs, in the form of a two-day workshop. Our training material is mainly aimed at graduate students outside the NLP sphere who have basic technical knowledge and wish to start working with text, is fully open source and available online.</abstract>
    <identifier type="citekey">daza-2026-hands-approach</identifier>
    <location>
        <url>https://aclanthology.org/2026.teachingnlp-1.7/</url>
    </location>
    <part>
        <date>2026-03</date>
        <extent unit="page">
            <start>37</start>
            <end>40</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era
%A Daza, Angel
%Y Aßenmacher, Matthias
%Y Biester, Laura
%Y Borg, Claudia
%Y Kovács, György
%Y Mieskes, Margot
%Y Serrano, Sofia
%S Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-375-3
%F daza-2026-hands-approach
%X With the advent of Large Language Models (LLMs) researchers outside the Natural Language Processing (NLP) field are interested in learning how to process textual data for their own domain research goals. They are particularly motivated to start experimenting directly with LLMs, implicitly neglecting the large amount of accumulated knowledge that NLP has to offer them. In this text, we briefly share our new lesson materials that aim to show aspiring practitioners the strong connection between NLP fundamentals and LLMs, in the form of a two-day workshop. Our training material is mainly aimed at graduate students outside the NLP sphere who have basic technical knowledge and wish to start working with text, is fully open source and available online.
%U https://aclanthology.org/2026.teachingnlp-1.7/
%P 37-40

Download as File

Markdown (Informal)

[A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era](https://aclanthology.org/2026.teachingnlp-1.7/) (Daza, TeachingNLP 2026)

A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era (Daza, TeachingNLP 2026)

ACL

Angel Daza. 2026. A Hands-on Approach to NLP Fundamentals for External Domain Experts in the LLM Era. In Proceedings of the Seventh Workshop on Teaching Natural Language Processing (TeachNLP 2026), pages 37–40, Rabat, Morocco. Association for Computational Linguistics.