Building Knowledge from Text: Methods, Models, and Practice

Every day, mountains of knowledge pile up as unstructured text and most of it never gets used. Learn how you can transform unstructured documents into actionable knowledge that supports informed, real-world decisions.

Large amounts of knowledge are created and stored every day as unstructured text, including articles, reports, notes, guidelines, and other sources from the World Wide Web. While rich in meaning, this information is often difficult to analyze systematically and remains unused when it comes to learning, reasoning, and decision making.

This training explores how unstructured text can be transformed into structured and usable knowledge. It examines the key challenges involved, such as ambiguity, context, scale, and credibility, and discusses approaches for extracting, organizing, and connecting information in ways that support understanding, insight, and automation.

The session introduces traditional and modern methods for working with natural language, including AI-based techniques and knowledge representations, and shows how they can help bridge the gap between text and insights. The focus is on concepts, patterns, and real-world considerations, making the course relevant for researchers, practitioners, and anyone interested in turning text into knowledge.

Agenda & Content

For a detailed timetable and additional information, please see Agenda & Content in the left menu.

Target audience, eligibility & prices

Everyone is welcome who wants to get a deeper understanding of how and why AI systems make decisions.

This course is open and free of charge for all participants from academia, industry, and public administration from EU and/or EuroHPC JU member countries.

Entry level & prerequisites

Basic – Participants are expected to be familiar with basic python programming, prior machine learning experience is not required.

Course format

This course will be delivered as a LIVE ONLINE COURSE (using Zoom).

Hands-on labs

All participants will get a temporary user account on one of the ASC systems to do the hands-on labs.

You will use your own laptop or workstation to connect conveniently from your browser to the ASC Jupyterhub and do the hands-on exercises on a suitable CPU or GPU partition of the ASC.

Accepted participants will be contacted a few days before the course and asked to do a short pre-assignment that has to be completed before the course starts.

Lecturer

Dr. Heidi Hobel (AIT Austrian Institute of Technology GmbH)                       
Dr. Heidi Hobel is a Research Engineer at the AIT Austrian Institute of Technology with over a decade of experience as an AI engineer, specializing in natural language processing and machine learning methods for semantic search, information extraction, and knowledge-based decision support. Her work focuses on transforming unstructured text into structured and enriched representations that enable systematic analysis and reasoning. She has extensive experience in text annotation and classification, as well as entity and relation extraction, and has applied these methods in real-world, interdisciplinary research and industry projects. She is passionate about connecting modern AI techniques with knowledge representation and supporting researchers and practitioners in effectively leveraging natural language technologies across a wide range of use cases.

Language

English

Date, time, and location

25.06.2026, 13:00 – 16:00 (CEST), LIVE ONLINE COURSE (Zoom)

Registration

Registration is required, the registration form can be found on top of this page in the menu on the left.

Please register with your official institutional email address to prove your affiliation.

You will get an automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders.

Following your successful registration, you will receive further information a few days before the course.

Please do not hesitate to contact us at training@ai-at.eu if you have any questions.

Waitinglist

After the number of registrations has reached its maximum or the registration form has been closed, you may want to send us an email (training@ai-at.eu) stating that you are interested to be put on the waiting list (vacancies may occur due to cancelations, etc.).

To be able to do the hands-on labs on the ASC systems please provide your full international mobile-phone number for the two-factor authentication required to login to the ASC systems.

Modification, withdrawal & no-show policy

Your registration is binding. Please only register for the course if you are really going to attend.

You can update your registration data or withdraw your registration anytime before the registration form has been closed via the link "Manage my registration" which you can find at the bottom of your automatic email confirmation (subject starting with "[Indico] Registration").

Alternatively, or after the registration form has been closed, please inform us about your cancelation or any change in your registration data (especially your mobile-phone number) via email (training@ai-at.eu).

No-show policy: If you do not cancel and do not show up at the course you will be blacklisted and excluded from future training events.

Organizers

This course is jointly organized by AI Factory Austria AI:AT and Austrian Scientific Computing ASC (aka ASC Research Center, TU Wien).

Acknowledgements

AI Factory Austria AI:AT has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101253078. The JU receives support from the Horizon Europe Programm of the European Union and Austria (BMIMI / FFG).