Date: 1 October 2026 Time: 12.30-13.30 Location: Online via Zoom
Join us for an introduction to UCloud and a guided tour of the platform’s latest features and updates following the migration to the new data center.
Whether you are new to UCloud or already using the platform, this webinar will help you navigate the platform, manage your projects and data, and make the most of the available applications.
In this session, you will learn how to:
Navigate the new UCloud interface and access your projects and resources.
Manage files and drives – create and organise project drives, upload and share data.
Explore the application catalogue and run applications on UCloud.
Understand the available compute resources and learn how to select the resources that best fit your research needs.
Target audience: Researchers, both new and existing UCloud users across all disciplines who want to get started with UCloud or learn more about the platform’s latest updates and features.
Technical level: Beginner to Intermediate. No prior experience with UCloud is required
CVAT, Computer Vision Annotation Tool, is an interactive video and image annotation tool, designed to facilitate the annotation of video and image data and accelerate the creation of high-quality datasets for computer vision tasks. CVAT is available on the UCloud platform, in the Application Store.
The webinar will show how to use CVAT on UCloud to:
Label and annotate data with the help of AI and OpenCV tools, including:
Use of cvat-cli
Run built-in model for detection and auto-annotation
Use of GPUS with built in models for faster annotation
Adding custom models (e.g. YOLO)
Efficiently manage large visual datasets with MinIO:
Allow CVAT to directly pull images from your UCloud MinIO buckets for annotation and export annotated data back, reducing manual imports/exports and ensuring data availability.
Using UCloud allows users to create fully reproducible and secure workflows that leverage high performance computing resources. Those features are often necessary for large dataset and accurate computer vision tasks.
Target audience: Researchers across all Departments, particularly who require high-precision data labeling, AI interested.
In this video tutorial you will watch a hands-on introduction to UCloud, the national research platform for compute, storage, and applications. The session is designed to help new users get started with UCloud and understand how to use the platform for research, teaching, and project work.
In the recording, we guide you through how to:
Log in to UCloud and navigate the dashboard
Understand key concepts such as projects, resources, and applications
Run your first job and apply for additional compute and storage resources
Manage files and collaborate using project workspaces
Explore the application catalogue and job submission options
Discover new features introduced in UCloud 4.0
This recording is relevant for students, researchers, and new UCloud users across all disciplines.
UCloud is beginner-friendly and does not require any technical background or prior experience with cloud computing.
Timestamps
00:00 – 02:20: Introduction What UCloud is, who it’s for, and what the webinar will cover.
02:20 – 03:50: Key terms you need to know Simple explanations of essential concepts used throughout the platform.
03:50 – 04:30: Support resources and useful links Where to find help on interactivehpc.dk and additional documentation.
04:30 – 06:10: Login process and UCloud dashboard overview How to log in and navigate the main dashboard.
06:10 – 08:30: Running your first job A quick walkthrough of launching an application on UCloud.
08:30 – 14:00: Applying for resources How to request compute and storage resources for your project.
14:00 – 17:20: File system and Drives How file storage works and how to manage your data.
17:20 – 18:00: Personal workspace vs project workspace Key differences and when to use each.
18:00 – 21:30: Managing a UCloud project Members, settings, allocations, and collaboration.
21:30 – 23:50: Resources page Public and IP links, SSH keys, and related settings.
23:50 – 25:40: Application catalogue and documentation How to find apps and access relevant guides.
25:40 – 28:50: Job submission page options Configuring applications before starting a job.
28:50 – 29:50: Running job view Monitoring jobs and understanding job status.
29:50 – 32:00: Work folder, output files, and Runs page Where to find results, logs, and job history.
32:00 – 35:40: What’s new in UCloud 4.0 Command palette, file tree, Syncthing and usage page.
35:40 – 36:08: Conclusion and next steps Summary and where to find further resources.
CVAT, Computer Vision Annotation Tool, is an interactive video and image annotation tool, designed to facilitate the annotation of video and image data and accelerate the creation of high-quality datasets for computer vision tasks. CVAT is available on the UCloud platform, in the Application Store.
The webinar will show how to use CVAT on UCloud to:
Label and annotate data with the help of AI and OpenCV tools, including:
Use of cvat-cli
Run built-in model for detection and auto-annotation
Use of GPUS with built in models for faster annotation
Adding custom models (e.g. YOLO)
Efficiently manage large visual datasets with MinIO:
Allow CVAT to directly pull images from your UCloud MinIO buckets for annotation and export annotated data back, reducing manual imports/exports and ensuring data availability.
Using UCloud allows users to create fully reproducible and secure workflows that leverage high performance computing resources. Those features are often necessary for large dataset and accurate computer vision tasks.
Target audience: Researchers across all Departments, particularly who require high-precision data labeling, AI interested.
Date: 19 February 2026 Time: 13:15 – 14:30 (CET) Location: Online, via Zoom
The purpose of this webinar is to demonstrate how to perform automated text classification using pre-trained, open-source large language models (LLMs). The efficiency that LLMs bring to otherwise laboursome workflows, such as text classification, makes it possible to work with much larger text corpora across all fields of research. The use case will focus on classifying text according to sentiment, but the general workflow is applicable to many other text classification tasks.
In the webinar, we will create a complete workflow which will consist of the following parts:
Retrieving text data from online sources
Storing and preparing the data for analysis
Setting up the LLM text classifier
Performing the text classification
Displaying the results (for validation etc.)
The workflow will be set up on the UCloud platform. Using UCloud allows users to create fully reproducible and secure workflows that leverage high performance computing resources which are often necessary to run LLMs locally.
In this webinar recording, you will watch a hands-on workshop introducing Dictaphone – a UCloud application that enables researchers to securely record and transcribe interviews directly from their own devices, even when working with sensitive data.
In the recording, we guide you through how to:
Record interviews and conversations using Dictaphone on your laptop or smartphone Audio is streamed in real time to the secure UCloud backend, ensuring that no data is stored locally on your device – making Dictaphone well suited for handling sensitive data.
Automatically transcribe recordings within the same workflow Dictaphone includes built-in transcription functionality, allowing you to convert speech to text quickly and efficiently.
Make the most of Dictaphone, including tips, additional features, and real research use cases.
This recording is relevant for researchers across all departments as well as students.
Dictaphone is a beginner-friendly application and does not require any technical background.
Time stamps
00:00 – 06:25: Introduction and getting started Requirements, data classifications, and the basic workflow.
06:25 – 32:15: Live demonstration of Dictaphone How to record and transcribe, and how to navigate the platform before and after recording.
32:15 – 33:50: Data storage and security How Dictaphone stores data and why it is suitable for sensitive data.
33:50 – 35:30: Related resources and support Other webinars, related UCloud apps, and contact information.
35:30 – 43:15: Q&A session Questions from the participants.
43:15 – 44:22: Wrap-up and next steps Summary and where to find further resources.
Date: 4 December 2025 Time: 13:00 – 14:00 (CET) Location: Online, via Zoom
Join us for a hands-on webinar introducing RAGFlow, an advanced Retrieval-Augmented Generation (RAG) platform available on UCloud. RAGFlow enables you to build your own intelligent assistants by combining document retrieval, embeddings, and large language models – all within a user-friendly visual interface.
In this session, you will learn how to:
Launch RAGFlow on UCloud – explore the application options in the job page and understand how to configure your workspace.
Navigate the RAGFlow interface – get familiar with the main dashboard, menus, and workflow structure.
Set up an embedding and chat model – choose from available models and understand their roles in retrieval and dialogue generation.
Create and manage knowledge bases – upload and process your own datasets, configure chunking and embedding strategies, and test retrieval quality.
Build a chat assistant – connect your models and knowledge base to create an interactive, context-aware chatbot.
Design a basic agentic workflow – combine tools and steps in RAGFlow’s visual builder to automate reasoning and responses.
Launch RAGFlow on UCloud – explore the application options in the job page and understand how to configure your workspace.
All workflows will be demonstrated live on UCloud, showing how to go from data ingestion to an operational AI assistant – no coding required.
Target audience: Researchers, students, and AI-curious users interested in document-based question answering, knowledge management, and conversational AI.
Technical Level: Beginner to Intermediate — no prior experience with RAG or model configuration needed. Basic familiarity with UCloud will be helpful. If you’re new to the platform, we recommend signing up for the Getting Started with UCloud workshop on 19 November
RAGFlow is a new application being introduced on UCloud this December. It lets you build your own smart assistant using your documents. It combines search and AI to answer questions based on information you provide – no coding required.
Key features:
Create your own knowledge base Upload PDFs, text files, or notes and let RAGFlow organize them for easy retrieval.
Choose AI models Pick an embedding model for search and a chat model for conversations, all within the app. You can also add other model types – such as reranking for better answer accuracy, speech-to-text for audio input, image-to-text for scanned documents, or text-to-speech for spoken responses.
Chat with your data Ask questions and get context-aware answers directly from your uploaded materials.
Simple visual workflow Set up each step through an easy, guided interface.
Secure on UCloud All data stays private and runs safely within UCloud’s secure environment.
RAGFlow is perfect for beginners who want to explore how AI can search, summarize, and explain their own research data or learning materials. For advanced users, RAGFlow also offers powerful customization through agentic workflows, where multiple models and tools can work together in sequence.
Keep an eye on updates here or in the UCloud app catalogue to be the first to know when RAGFlow becomes available.
Date: 19 November 2025 Time: 13:00 – 14:30 (CET) Location: Online, via Zoom
Join us for a hands-on workshop where we guide you through the main features and new tools on UCloud, the national research computing platform that brings together data storage, computation, and collaboration in one place.
In this session, you will learn how to:
Navigate the UCloud interface – understand the menus, and dashboard to access your projects and resources efficiently.
Manage files and drives – create and organise project drives, upload and share data, and use the new integrated file editor, terminal and search.
Work with projects – set up collaborative projects, manage members and permissions, and monitor resource allocations.
Run applications on UCloud – explore the application catalogue, launch and monitor jobs, and use application documentation.
Use the latest UCloud features – discover new tools such as the Command Palette for quick actions, integrated Terminal for lightweight file management, real-time job metrics and improved Usage and Allocations pages.
Target audience: Staff, researchers, students, and new UCloud users across all disciplines who want to understand how to get started with UCloud and make the most of its latest features.
Technical Level: Beginner to Intermediate — no prior experience with UCloud required.
Date: 26 November 2025 Time: 12:30 – 13:30 (CET) Location: Online, via Zoom
Join us for a hands-on workshop where we introduce Dictaphone – a new UCloud application that allows researchers to securely record and transcribe interviews directly from their own devices.
In this session, you will learn how to:
Use Dictaphone to record interviews and conversations directly from your laptop or smartphone. The recordings in Dictaphone are streamed in real time to the secure UCloud back end – ensuring that no data is stored locally on your device, making the app ideal for working with sensitive data.
Transcribe recordings automatically within the same workflow. Dictaphone has built-in transcription functionality, enabling you to easily convert speech to text and streamline your interview process.
How to make the most of Dictaphone — with tips, extra features, and real research use cases.
Target audience: Researchers across all departments, students, those interested in AI.
Technical Level: Basic to Intermediate – beginner-friendly and requires no technical background. Basic familiarity with UCloud will be helpful. If you’re new to the platform, we recommend signing up for the Getting Started with UCloud workshop on 19 November
Dictaphone is a new application being introduced on UCloud this November. It allows researchers to securely record and transcribe interviews and conversations directly from their own devices – making the interview process easier and more time-efficient.
Key features:
Record directly from your device Use Dictaphone to capture interviews and conversations straight from your laptop or smartphone. The user interface is simple to use and optimised for viewing on both small and large screens.
No local storage – full data security All recordings are streamed live to the secure UCloud backend. Nothing is saved on your device, which means you can safely handle sensitive data without worrying about your data being stored in an unsafe location.
Built-in transcription Dictaphone includes built-in transcription functionality, enabling you to easily convert speech to text and streamline your interview process.
Speaker recognition The app can distinguish between multiple speakers in the same recording, making transcripts easier to read and analyse for interviews or group discussions.
The Dictaphone app is designed for researchers across all disciplines who record audio as part of their work. It supports different workflows – whether you prefer to transcribe after each question in your research process or after the full interview, you can use Dictaphone. You can also switch languages, making it ideal for both Danish and international projects.
Keep an eye on updates here or in the UCloud app catalogue to be the first to know when Dictaphone becomes available.
In this video we will guide you through the complete pipeline of fine-tuning large language models (LLMs) for specialised tasks such as medical question-answering using NeMo Framework and Triton Inference Server.
Prepare and preprocess open-source datasets for fine-tuning.
Apply Parameter-Efficient Fine-Tuning (PEFT) using LoRA with NVIDIA NeMo Framework.
Deploy optimised LLMs using NVIDIATriton Inference Server and TensorRT-LLM.
Generate a synthetic Q&A dataset using Label Studio connected to a live inference backend.
Fine-tune and evaluate your customised LLM for domain-specific applications.
All workflows will be executed inside a UCloud project environment with access to GPU resources.
Target audience: Machine learning practitioners, researchers, and engineers interested in LLM customisation, domain adaptation, or scalable model deployment.
