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Short course: Modern Conversational AI — From Classic NLU to LLMs

This short course covers the foundations of conversational systems—classic NLU (intents, entities, slot filling, dialogue design) and modern LLM workflows (prompt engineering, function calling, RAG). Participants build a practical chatbot grounded in their own documents, evaluate quality and safety, and deploy a lightweight interface. An HPC module is included for large-scale embeddings and offline evaluation/load testing.

  • Date: 21.11.2025 at 11:45
  • Venue: PS, UDG
  • Registration required: https://forms.gle/SRW6GYiRAbi8pFBe8
  • Designed for: students, researchers, and professionals with basic Python and web/API skills.
Short course on NLP and LLMs

Course content overview

Session 1 (90 min) – theoretical framework

  • From classic NLU (intents/entities/slots) to LLM “agents”
  • Dialogue design: state machines vs. tools/functions
  • RAG essentials: indexing, chunking, hybrid search, source citations
  • Evaluation & safety: relevance/groundedness, moderation, PII
  • HPC view: when batch embeddings and batch evaluation matter

Session 2 (90 min)- hands-on lab

  • Project setup and starter RAG pipeline
  • Document import/index, prompt + function calling
  • Quick evaluation and guardrails
  • Deploy a web chat

Learning outcomes

  • Contrast intent-based vs. LLM-based chatbots.
  • Design dialogue and implement a grounded RAG pipeline with citations.
  • Ship a lightweight production chatbot with evaluation and safety.
  • Apply HPC techniques to scale embeddings and offline performance testing.
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EuroCC Researchers Participate in the Montenegrin Machine Learning Workshop

Researchers from EuroCC Montenegro participated in the Montenegrin Machine Learning Workshop, a one-day event aimed at popularizing topics related to Machine Learning (ML) and Artificial Intelligence (AI) among students, researchers, and practitioners. The workshop was organized in cooperation with the Montenegrin Artificial Intelligence Association (MAIA) as a satellite event to the EEML summer school. Participants attended lectures covering deep learning and its applications in earth observation, graph neural networks, power grids, biology and genomics.

During the poster session, visitors had the opportunity to learn more about the EuroCC project and its efforts to promote AI and HPC research in Montenegro.

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Two AI Short Courses Successfully Completed by NCC Montenegro

Over the past two weeks we delivered two focused courses, conducted under the EUROCC 2 & EUROCC4SEE project, with an outstanding cohort of participants — students, researchers, and professionals who excelled in curiosity, teamwork, and results.

Dejan Babic giving presentation on CV &CNN supported by HPC

Computer Vision & CNNs with HPC – Short Course

  • From raw pixels to features and robust visual representations
  • Hands-on lab: building and training an image classifier
  • Running experiments on the NCC Montenegro HPC cluster
  • Participants mastered concepts quickly, asked sharp questions, and worked independently in the lab
Ivan Jovovic, giving a presentation on Edge/AI supported by HPC

EdgeAI – Artificial Intelligence & the Internet of Things supported by HPC

  • Designing efficient AIoT data pipelines
  • Deciding when to process at the edge vs. in the cloud
  • Deploying lightweight ML models on resource-constrained devices
  • Model optimization using HPC infrastructure
Demonstration by Elvis Taruh and Ivan Jovovic on running HPC created models on NVidia Jetson platform

Stay tuned for the next sessions and advanced workshops!

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HPC Development for Very-High-Resolution Atmospheric Reanalysis in Montenegro

The Institute of Hydrometeorology and Seismology of Montenegro successfully secured HPC access from the EuroHPC JU Development Call for their project titled:
“HPC Development for Very-High-Resolution Atmospheric Reanalysis Using a Nonhydrostatic Mesoscale Model over Montenegro (1995–2024)”. The project aims to enhance mesoscale weather modeling capabilities using the WRF-NMM (Nonhydrostatic Mesoscale Model) and to investigate the scalability and performance of nonhydrostatic dynamic cores on state-of-the-art high-performance computing (HPC) architectures.

Through this initiative, the project was granted 4,000 node hours on the LUMI-C partition for a period of six months. The National Competence Centre (NCC) Montenegro provided support throughout the project application process.

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Representatives of NALED and Philip Morris International visited UDG, NCC Montenegro, and CoE FoodHub

Representatives of NALED and Philip Morris International visited UDG, NCC Montenegro, and CoE FoodHub

Representatives of NALED (National Alliance for Local Economic Development), Serbia, and Philip Morris International visited the University of Donja Gorica, where they presented their leading projects — StarTech, Empower Innovation, and particularly PMInnovia — aimed at connecting science and industry, promoting the concept of open innovation, and supporting researchers and innovators in developing ideas to improve products, processes, and the competitiveness of the economy.

During the visit, the representatives of NALED and PMI were introduced to the research and project activities of UDG, the National Competence Center for Supercomputing (NCC Montenegro), and the Center of Excellence for Digitalization of Food Safety Risk Assessment and Precision Certification of Food Product Authenticity (CoE FoodHub), particularly in the areas of HPC and AI technology applications and support for digital innovations in smart agriculture, personalized medicine, monitoring the authenticity of Montenegrin food products, and bioinformatics for genomic profiling.

The delegation also toured the Virtual Reality (VR) and 3D Printing Laboratory, where student projects showcasing the connection between technology, robotics, research creativity, and industrial relevance were presented. They also visited the Food Safety and Quality Laboratory, where modern methods and equipment for physico-chemical and microbiological analyses were demonstrated, as well as the Entrepreneurial Nest, where they learned about business initiatives supporting innovation and students, such as UDG’s StartUp program and the Entrepreneurial Ideas Exchange.

The professional discussion focused on mapping regional expertise, biotechnological innovations, and exploring potential collaboration within interdisciplinary teams sharing a common vision of advancing the innovation ecosystem and the economic development of the region.

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NCC Montenegro Strengthens Collaboration through Mentoring/Twinning Sessions with NCC Latvia and NCC Spain

As part of ongoing EuroCC2 collaboration, NCC Montenegro participated in two mentoring/twinning online sessions with partner NCCs to exchange knowledge and share best practices and improve internal processes for seamless interaction and  integration within the HPC/AI national ecosystem.

The first session, held with NCC Latvia on 22 October 2025, focused on Customer Relationship Management (CRM) tools and effective practices for managing project communications, coordinating client interactions, and tracking HPC/AI user data. NCC Latvia representatives provided a live demonstration of CRM workflows, offering practical insights and best approaches to streamline internal processes and monitor engagement with NCC services.

The second session, organized with NCC Spain on 31 October 2025, addressed Newsletter strategies for improving service visibility and customer outreach. Discussions included digital communication/ marketing tools, techniques for crafting engaging content, balancing updates on upcoming activities with past achievements, segmenting audiences effectively, and leveraging analytics to measure impact.

These mentoring sessions contribute to NCC Montenegro’s continuous efforts to enhance internal efficiency, optimize service delivery, expand outreach capacity, and strengthen stakeholder engagement.

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Artificial intelligence and the internet of things – EdgeAI

This focused short course explores how artificial intelligence (AI) can be embedded into Internet of Things (IoT) systems, with a special emphasis on edge AI – running ML models directly on devices, close to where data is generated. Participants will learn how to design AIoT pipelines, when to process data on the edge vs. in the cloud, and how to deploy lightweight ML models on resource-constrained hardware. The course is intended for students, researchers, and professionals who want to move from “connected devices” to intelligent devices.

Course date: 05.11.2025 at 13:30
Venue: S34, UDG
Registration: required
Registration link: https://forms.gle/2DktEUqf5KZosFth7

Designed for: students, researchers, and professionals interested in AI, IoT, edge computing and applied ML.

Course Content Overview

Session 1 — AI + IoT theoretical framework

  • AI–IoT convergence: from sensing to intelligent action
  • edge vs. cloud vs. fog: latency, bandwidth, privacy, cost
  • edge AI pipeline: device → preprocessing → inference → actuation
  • lightweight/embedded ML (TinyML, quantization, pruning)
  • platforms and use cases (Raspberry Pi, Jetson, smart agriculture, industry)

Session 2 — hands-on edge/AI lab

  • preparing the edge/IoT environment and data source (sensor/camera/mock)
  • deploying a small ML model to the device
  • running inference locally and sending results to backend/cloud
  • monitoring and simple performance checks
  • how to scale to real deployments

Learning outcomes

By the end of the course, participants will be able to:

  • explain the relationship between AI, IoT and edge computing
  • decide when inference should run on the device and when in the cloud
  • deploy a lightweight ML model to an IoT/edge setup
  • outline an end-to-end AIoT application for their own domain (e.g. agriculture, smart city, industry)
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