0.6 open-source-ai-workshops-2026 2026-05-18 2026-05-19 2 00:05 https://pretalx.com Europe/Berlin Raum A Workshop 2026-05-18T09:00:00+02:00 09:00 08:00 In diesem Workshop werden die Grundlagen von AI vermittelt. Wie funktioniert (Generative) KI, was sind Transformer Modelle und wie werden basierend darauf Large Language Modelle (LLMs) entwickelt. Der Workshop versucht so gut wie möglich ohne Mathematik auszukommen, sondern die Konzepte so weit zu vermitteln, dass ein Verständnis dafür entsteht. In einem zweiten Teil wird vermittelt wie LLMs auf lokalen Geräten unter Einhaltung des Datenschutzes angewendet werden können. Dies machen wir anhand des Beispiels von LM-Studio, welches die Verwendung von LLMs auf lokalen Geräten ermöglicht. open-source-ai-workshops-2026-88777-einfuhrung-zu-open-source-ai Gygli Marcel de Folgende Themen werden behandelt: - Was sind Transformer-Modelle und wie funktionieren sie? - Wie funktioniert Generative KI? - Lokale Nutzung von LLMs mittels ollama / LM-Studio - Wie funktioniert Retrieval Augmented Generation (RAG)? - Wie baue ich einen RAG-Chatbot auf meinen eigenen Dokumenten mit Open Source AI? Zusätzliche Diskussionsthemen, die im Rahmen des Workshops auf Wunsch angesprochen werden können: - Ethische Aspekte von KI (Bias, Fake News, Verantwortung) - Open-Source vs. Closed-Source KI-Modelle - Die Zukunft von LLMs und personalisierter KI false https://pretalx.com/open-source-ai-workshops-2026/talk/EBTWDL/ https://pretalx.com/open-source-ai-workshops-2026/talk/EBTWDL/feedback/ Raum B Workshop 2026-05-18T09:00:00+02:00 09:00 08:00 AI-powered autonomous agents are changing the way we interact with large language models (LLMs). In this hands-on workshop, you will learn how to build and customize AI agents using open-source models and frameworks. We will explore how these agents reason, plan, and execute tasks, and how they can be integrated with external tools. This workshop is designed for developers, researchers, and AI enthusiasts who want to build intelligent LLM applications. No prior experience with AI agents is required—just basic Python knowledge and a curiosity to experiment! --- After the workshop you will know... --- ✅ What AI agents are and how they interact with LLMs ✅ How to build AI-driven workflows using open-source frameworks ✅ How to integrate external tools and APIs using MCP ✅ How to secure your agents using guardrails ✅ How context engineering can be used to reduce hallucinations open-source-ai-workshops-2026-88790-ai-agents-in-action-building-smart-open-source-llm-workflows Luca Rolshoven de AI agents allow large language models to go beyond simple text generation—they can think, plan, and take action. In this workshop, we will explore how to design LLM-powered agents that automate workflows, process information, and interact with external systems. In this workshop you will be able to choose among many different cloud-based LLMs to gather hands-on experience with agentic AI. You’ll start by building a simple AI agent, then extend it with new capabilities, such as integrating APIs or working with structured data. --- Key Topics Covered --- ✔ Understanding AI Agents: What they are, how they work, and common frameworks ✔ Hands-on Development: Building a simple agent from scratch ✔ Expanding Capabilities: Enhancing agents with plugins, APIs, or external tools ✔ Optimizing Agent Performance: Debugging, logging, and prompt tuning ✔ Guardrails: Securing your agentic workflows ✔ Context Engineering: How to reduce hallucinations --- Who Should Attend? --- 👨‍💻 Developers interested in LLM-powered automation 📊 Data scientists & AI researchers exploring autonomous AI workflows 🛠️ Tech enthusiasts looking for hands-on experience with AI agent frameworks --- Prerequisites --- • Basic Python programming skills • Familiarity with Git & working in a terminal • Some knowledge of LLMs (not required but helpful) • A laptop with Python 3.11+ installed, or the ability to use a cloud-based environment false https://pretalx.com/open-source-ai-workshops-2026/talk/HY8GHW/ https://pretalx.com/open-source-ai-workshops-2026/talk/HY8GHW/feedback/ Raum C Workshop 2026-05-18T09:00:00+02:00 09:00 08:00 Kann **ein Team** ohne Vorlage in **6 Stunden** ein **funktionierendes RAG-System** bauen – nur mit einem Open-Source-Coding-Agenten und einer API-Spezifikation? Wir probieren es aus. open-source-ai-workshops-2026-89854-das-vibe-coding-experiment-vier-teams-sechs-stunden-ein-ziel Joel Barmettler de Vier Teams übernehmen je eine Kernkomponente: LLM-Inference-Server, Vektor-Datenbank, Dokument-Prozessor und Chat-Frontend. Jedes Team baut seine Komponente from scratch, ohne fertige Frameworks – nur mit Basislibraries und opencode-ai als Copilot. Am Ende integrieren wir alles live zu einem funktionierenden Gesamtsystem. Wir arbeiten durchgehend mit offenen Technologien: opencode-ai als Coding-Agent, Open-Weights-Modelle wie DeepSeek oder GLM-4, und das finale System läuft auf einem lokalen Open-Source-LLM. **ABLAUF** Der Workshop besteht aus vier Sessions: 1. **Fundament** – Systemarchitektur verstehen, Einführung in opencode-ai, Teambildung 2. **Verstehen & Planen** – Teams erarbeiten ihre Komponente, erstellen eine Kurzpräsentation 3. **Bauen** – Implementation der Kernfunktionalität, Zwischenstand 4. **Integrieren** – Komponenten zusammenführen, Live-Demo, Reflexion **FÜR WEN** Für alle, die verstehen wollen, wie KI-Systeme unter der Haube funktionieren, und AI-gestütztes Programmieren mit Open-Source-Tools ausprobieren möchten. Du musst kein erfahrener Entwickler sein – wichtiger ist die Bereitschaft zu experimentieren. **VORAUSSETZUNGEN** - Laptop mit Browser - GitHub-Account Alles andere läuft im vorkonfigurierten GitHub Codespace. **WAS DU MITNIMMST** - Praktische Erfahrung mit Vibe Coding - Verständnis der Kernkomponenten eines RAG-Systems - Deinen eigenen Code zum Weiterbauen false https://pretalx.com/open-source-ai-workshops-2026/talk/YZ8W7Y/ https://pretalx.com/open-source-ai-workshops-2026/talk/YZ8W7Y/feedback/ Raum A Workshop 2026-05-19T09:00:00+02:00 09:00 08:00 As robotics and AI systems move rapidly into industrial environments, compliance, safety, and ethical governance have become strategic enablers—not blockers—of innovation. In this hands-on workshop, you will learn how to apply the newly developed “11 Key Elements for Achieving AI & Robotics Compliance in 2025 and Beyond” to your own industry context. Through interactive exercises, group work, and case-based simulations, you will explore how organizations can operationalize ethical AI, prepare for emerging regulations, and embed governance as a driver of trust, performance, and resilience. This workshop is ideal for professionals across sectors who want practical tools for adapting AI governance frameworks to industrial, public-sector, and cross-organizational environments. open-source-ai-workshops-2026-88631-robotics-ethical-ai-in-industry-how-to-apply-the-11-element-compliance-framework-hands-on-cross-industry-edition Kateryna Portmann de You will learn: ✅ How to adapt the framework to your own industry (manufacturing, logistics, healthcare, public sector, mobility, etc.) ✅ How governance acts as an innovation catalyst, not just a regulatory requirement ✅ How to map real-world use cases to risk classes and compliance expectations ✅ How to align stakeholders (technical + legal + business) using a shared model ✅ How to evaluate maturity and readiness within your organization ✅ Bonus: Creating a quick-start “AI Governance Canvas” you can take home false https://pretalx.com/open-source-ai-workshops-2026/talk/YSWYU8/ https://pretalx.com/open-source-ai-workshops-2026/talk/YSWYU8/feedback/ Raum B Workshop 2026-05-19T09:00:00+02:00 09:00 08:00 In this workshop, we will introduce the ideas behind Agentic AI systems using a recently introduced protocol called Model Context Protocol or MCP [Please see https://en.wikipedia.org/wiki/Model_Context_Protocol]. Throughout the day of the workshop, we will plugin various tools to the LLM using MCP servers and show you how you can implement it for your own work. This is a full day hands-on technical workshop. NOTE: - The workshop will be held in English. - We will be using Anthropic Desktop Claude as our LLM [Please see https://claude.com/download]. It would be great if you can download the application of your machines and create an account. Please note that you can use the free version but it will have limits [Please see https://support.claude.com/en/articles/8602283-about-free-claude-usage]. - We also expect that you will have access to tools like Github - If you do not know how to code, you can just use your favourite LLM to generate code during the workshop. open-source-ai-workshops-2026-88573-empowering-ai-agents-building-intelligent-ai-agents-via-mcp /media/open-source-ai-workshops-2026/submissions/QSLE3B/Model_QIcI5TI.webp Sid Singh de The broad topics that will be covered are (but not limited to): - Introduction to Agentic AI systems: background, Basic concepts - Introduction to MCP: What is it, What problems is it solving - How to write an MCP server: Local and Remote - Implement a use-case using MCP - Use your own use-case and implement it We (highly) encourage you to bring your own datasets or API access so that you can use them to implement your use-case with an MCP server (using Anthropic Claude). You should, of course, keep in mind regulations and privacy laws that apply to your data/API access. false https://pretalx.com/open-source-ai-workshops-2026/talk/QSLE3B/ https://pretalx.com/open-source-ai-workshops-2026/talk/QSLE3B/feedback/ Raum C Workshop 2026-05-19T09:00:00+02:00 09:00 08:00 Ever wished your AI could do more than just answer a question? What if you could teach it how to think, decide, and verify? This workshop introduces one of the newest and most powerful AI architectures: graph-based reasoning systems, where AI agents follow structured decision graphs to retrieve information, reason step by step, and produce reliable, evidence-based answers. We begin from first principles, explaining how large language models work and why they cannot be trusted on their own. You will then build a complete RAG pipeline that connects an open-source LLM to real documents, enabling it to retrieve evidence and generate fact-grounded answers instead of confident guesses. From there, we move beyond linear pipelines. You will transform your RAG system into a graph-based AI agent: an autonomous assistant whose reasoning is explicit, structured, and controllable. Using a reasoning graph, the AI learns when to retrieve information, how to combine multiple sources, when to verify results, and when to stop. Instead of one-shot responses, your system follows a clear decision flow that mirrors human problem-solving. By the end of the workshop, you will have built a complete, open-source AI assistant that can read documents, retrieve knowledge, reason through a graph, and answer with evidence. Not a simple chatbot. A truly intelligent AI agent that follows a path of thought. open-source-ai-workshops-2026-88603-designing-thinking-machines-the-future-of-ai-with-graphs-based-ai-agents Ornella Vaccarelli de ## What you will learn: - **Master the Fundamentals** : Learn how Retrieval-Augmented Generation (RAG) and AI agents work together to combine retrieval, reasoning, and generation into accurate, context-aware responses. - **Build Your Own AI Agent System**: Follow a step-by-step process to build the full pipeline from document ingestion, chunking, embeddings, retrieval, to LLM integration, and then upgrade it into a graph-based agent that knows when to retrieve, what to search, and how to produce grounded answers. - **Gain Hands-On Experience**: Work through practical exercises and real-world examples that show how a graph-based agent can explore different type of documents, gather evidence, verify key points, and answer in a reliable way. - **Ensure Data Security**: Learn how to deploy open-source AI systems with a strong focus on data privacy, secure processing, and responsible use of sensitive information. - **Bonus: Evaluation & Reliability**: Discover how to test and measure your AI system to ensure it is using the right sources, avoiding hallucinations, and producing reliable, trustworthy answers. ## Who Should Join This workshop is designed for anyone familiar with Python who wants to go deeper into how the most robust and modern AI systems are built. Perfect for: 💻 Developers 📊Data Scientists 🛠️Engineers 🤖Curious AI Enthusiasts Some experience with Python programming is required. You don’t need any background in machine learning or artificial intelligence. We’ll build everything together, step by step. ## What to Bring Just bring your laptop and a stable internet connection (Wi-Fi). We’ll take care of the rest. ## Why This Matters Most LLMs are impressive… but also a little dangerous. They often sound confident even when they are wrong. In this workshop, you will build an AI system where RAG provides knowledge, AI agents add judgment and graph-based reasoning allows your AI to search, verify, and think (in the right way) before it answers. false https://pretalx.com/open-source-ai-workshops-2026/talk/SVYPLV/ https://pretalx.com/open-source-ai-workshops-2026/talk/SVYPLV/feedback/ Raum D Workshop 2026-05-19T09:00:00+02:00 09:00 05:00 Dieser Workshop vermittelt Entscheidungstragenden eine fundierte Einführung in die Entwicklung und den Betrieb von Open Source KI rund um technische, rechtliche und praktische Aspekte. Neben den Vorteilen wie Kosteneffizienz und digitale Souveränität werden auch Herausforderungen wie technische Hürden und juristische Fragen beleuchtet, um Führungskräften, IT-Verantwortlichen und Innovationsmanagern fundierte Entscheidungsgrundlagen zu bieten. open-source-ai-workshops-2026-89125-einfuhrung-open-source-ai-fur-entscheidungstragende /media/open-source-ai-workshops-2026/submissions/DRDPRE/image_j4oELtU.jpg Matthias StürmerCH Open de Die rasante Entwicklung künstlicher Intelligenz (KI) eröffnet vielfältige Möglichkeiten für Unternehmen und Behörden. Open Source KI-Modelle wie DeepSeek und über 2.7 Millionen weitere Modelle auf Hugging Face spielen dabei eine zentrale Rolle, da sie Innovation, Transparenz und Anpassungsfähigkeit fördern. Wie funktioniert Open Source KI, wie werden sie konkret angewendet und welche Chancen und Herausforderungen ergeben sich aus der Nutzung von Open Source KI? Dieser Workshop bietet Entscheidungstragenden eine fundierte Einführung in die Entwicklung und den Betrieb von Open Source KI mit einem technischen Überblick, Einblick in rechtliche und ethische Aspekte und zahlreichen Beispielen aus der Praxis. Wir beleuchten die Vorteile wie Kosteneffizienz, Innovationsbeschleunigung und Unabhängigkeit von proprietären Anbietern (digitale Souveränität), diskutieren aber auch Herausforderungen wie technische Hürden, wirtschaftliche Fragen und die Notwendigkeit von internem Knowhow. Der Workshop richtet sich an Führungskräfte, IT-Verantwortliche sowie Projekt und Innovationsmanager, die fundierte Entscheidungen zur Nutzung von Open Source KI in ihrer Organisationen treffen möchten. Der Hauptdozent ist Prof. Dr. Matthias Stürmer, Leiter des Instituts Public Sector Transformation der BFH. Als Gastreferierende werden Luca Rolshoven (Informatik-Doktorand) und Veton Matoshi (NLP-Spezialist) Beiträge halten. Das Programm ist wie folgt: 09:00h Überblick Open Source AI -> Matthias Stürmer (BFH) Kurze Vorstellungsrunde, Fragen abholen, Definition digitale Souveränität und Open Source AI, Einführung KI, LLMs, Pre-Training, Fine-Tuning etc. 10:30h Pause 11:00h Natural Language Processing (NLP) -> Veton Matoshi (BFH) Verarbeitung von Text in Machine Learning Verfahren, Vektorisierung von Wörtern und Sätzen, Transformers, Praktische Beispiele mit Python, spaCy und Jupyter Notebooks 12:30h Mittagspause 13:30h Deep-Dive in Open Source AI -> Luca Rolshove (BFH) Aktuelle Tech-Trends in Open Source AI, Vergleich von Open Source und proprietären AI-Modellen, Benchmarks und Leaderboards 14:30h Pause 15:00h Anwendung von Open Source AI -> Matthias Stürmer (BFH) Betrieb von Open Source AI Modellen, Retrieval-Augmented Generation mit Open Source AI Modellen, Agentic AI und das Model Context Protocol (MCP) 17:00h Abschluss false https://pretalx.com/open-source-ai-workshops-2026/talk/DRDPRE/ https://pretalx.com/open-source-ai-workshops-2026/talk/DRDPRE/feedback/