| Start date: | 19 May 2026, 09:00 (CEST) | Entry level: | Basic | |
| End date: | 19 May 2026, 13:00 (CEST) | Subject area: | Artificial Intelligence (AI) | |
| Location: | ONLINE (Zoom) | Topics: | Bias in AI | |
| Language: | English | Target audience: | Industry, public admin, academia | |
| Price: | Free (for eligible participants) | Organizers: | AI:AT & ASC |
Detection and mitigation of bias in Artificial Intelligence (AI) projects isn’t just a technical nuisance. It’s a systemic design challenge, and fixing it requires collaboration between engineers, product owners, and leadership.
Building on our previous webinar Machine Learning and Human Prejudice: Understanding Bias in AI, this hands-on workshop brings the conversation into the codebase. Participation in the webinar is not a prerequisite for this course.
This session is designed for those who build, train, and deploy machine learning models, and who want to move beyond awareness into concrete action. Through guided notebook walkthroughs and a hands-on exercises, participants will explore how bias enters AI systems at the data, algorithm, and interpretation level, learn to measure fairness using industry-standard metrics, and apply mitigation techniques using libraries like IBM's AI Fairness 360. The session also covers documentation practices and post-deployment monitoring, so that fairness becomes a built-in habit rather than an afterthought.
Agenda & Content
For a detailed timetable and additional information, please see Agenda & Content in the left menu.
Target audience, eligibility & prices
Developers, ML engineers and Data scientists who build or work with machine learning models and want practical tools to detect and mitigate bias in their own pipelines.
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 – no prior knowledge of AI fairness or bias mitigation is needed, we start from the fundamentals.
Participants are expected to be familiar with Python and basic machine learning concepts (training/test split, model evaluation).
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
Giulia Bianchi (AIT Austrian Institute of Technology GmbH)
Giulia Bianchi is a Research Engineer at AIT Austrian Institute of Technology, where she leads the Machine Learning Group within the AI Task Force. With a background spanning linguistics and AI, she develops LLM-based systems including digital twins, chatbots, and knowledge extraction tools. Her work focuses on ensuring AI systems are not only technically robust but also fair and contextually appropriate across different user groups.
Language
English
Date, time, and location
19.05.2026, 09:00 – 13:00 (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).
