| Start date: | 3 March 2026, 16:00 (CET) | Entry level: | Intermediate | |
| End date: | 4 March 2026, 18:00 (CET) | Subject area: | Artificial Intelligence (AI) | |
| Location: | ONLINE (Zoom) | Topics: | Computer Vision (CV) | |
| Language: | English | Target audience: | Academia, industry, public admin | |
| Price: | Free (for eligible participants) | Organizers: | AI:AT & ASC |
The Computer Vision (CV) landscape has transformed dramatically. What once required weeks of manual annotation can now be accomplished in hours, or skipped entirely with open-vocabulary models. Learn about the newest toolkits and gain hands-on experience using them on a High-Performance Computing (HPC) system.
Modern toolkits allow much faster CPU inference than predecessors and enable real-time open-vocabulary detection with text prompts ("find all forklifts") or visual examples. The complete pipeline, from raw images to deployed model, takes under 2 hours.
This workshop introduces practitioners to modern toolkits, foundation model distillation via Autodistill, direct open-vocabulary detection with YOLOE-26, and edge-optimized deployment using YOLO26 (released January 14, 2026). Participants will learn to choose the right approach for their use case: auto-label datasets using SAM 3 and Grounding DINO, train lightweight YOLO26 models for edge deployment, or leverage YOLOE-26's text and visual prompts to detect arbitrary objects without any training at all.
Agenda & Content
For a detailed timetable and additional information, please see Agenda & Content in the left menu.
Target audience, eligibility & prices
Researchers, data scientists, ML engineers, and domain experts who want to:
- rapidly prototype computer-vision solutions without annotation budgets
- understand when to use open-vocabulary models vs. custom training
- deploy efficient edge models on constrained hardware
- leverage HPC infrastructure for scalable CV 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
Intermediate – Basic familiarity with machine learning concepts is expected.
Participants are expected to:
- have basic python programming skills
- be familiar with ML concepts (training, inference, datasets)
- know how to work on the Linux command line
- have a conceptual-level understanding of image classification and object detection
No prior experience with foundation models, transformers, or YOLO 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
Dejan Đukić (External)
Dejan Đukić is an AI Software Expert with an extensive background in computer vision (cloud and edge), bioinformatics, and agentic AI systems. He holds a Master’s degree in Life Science Informatics from Rheinische Friedrich-Wilhelms-Universität Bonn and is experienced in building production CV pipelines in clinical, medical device, and manufacturing startup environments.
Language
English
Date, time, and location
03. – 04.03.2026, 13:00 – 16:30 (CET), 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).
