Discover upcoming AI conferences in Munich for 2026.

AI Conferences in Munich 2026

### Overview
TDWI München 2026 is the annual conference dedicated to data, analytics, and artificial intelligence. Held at the MOC Munich from June 23 to June 25, 2026, the event is described as independent and vendor-neutral, offering a broad and deep program that covers current trends and established technologies in the data domain. The conference is positioned as a knowledge hub and networking platform for practitioners across roles, including business analysts, data scientists, data engineers, data architects, and leadership in data initiatives. The program has been published for 2026 and promises a comprehensive look at the data universe, analytics practices, and AI innovations.

### What to expect
Participants can look forward to a large program with more than 130 sessions delivered over three days, featuring a mix of talks, hands-on sessions, and interactive formats. The event highlights practical use cases, data strategy, governance, modern data architectures, and AI-powered solutions. The conference emphasizes real-world relevance and knowledge depth, rather than a call-and-response show, with speakers drawn from across the data and analytics ecosystem. In addition to formal sessions, there is a robust agenda of networking opportunities, expo offerings, and social events designed to foster collaboration and inspiration.

### Agenda and sessions
The TDWI München program spans three days, with a variety of conference tracks and sessions intended to address the needs of different professional profiles. The content includes keynote talks, technical sessions, and interactive formats such as hands-on workshops. The program emphasizes practical learning and industry relevance, aiming to equip attendees with actionable insights for data-driven decision making, data governance, and AI deployment. The event also promotes engaging formats like dashboard karaoke and Fishbowls as part of the program experience.

### Speakers and perspectives
The conference welcomes more than 100 sessions led by over 150 industry experts and practitioners. Speakers come from diverse backgrounds, including data engineering, data science, analytics, AI, and data strategy. Attendees can expect a range of perspectives from practitioners who are actively implementing data initiatives in organizations, offering deep dives into techniques, architectures, and real-world challenges.

### Format and venue
TDWI München 2026 is described as an in-person conference with a comprehensive program, an expo featuring technology partners, and multiple networking opportunities. The event format is designed to facilitate exchanges among peers, with ample time for discussions, demonstrations, and hands-on exploration of data technologies. The venue, the MOC München, provides a setting conducive to deep dives into data topics while allowing attendees to connect with colleagues and potential collaborators.

### Who should attend
The conference is suitable for data engineers, architects, scientists, analysts, ML engineers, project leads, and IT leadership who work with data, analytics, and AI. It is positioned as ideal for anyone seeking to advance data-driven decision making, implement AI or analytics initiatives, or explore new tools and methodologies in a vendor-neutral environment.

### FAQ
- Where is the event held? MOC München, Germany.
- When is it? June 23 to June 25, 2026.
- How many sessions are expected? Over 130 talks across three days, with more than 150 speakers.
- Is the event online or in person? In person, with on-site networking and expo activities.


TDWI München 2026

Artificial Intelligence (AI) conference in Munich, Germany

VibeKode

Machine Learning (ML) conference in Munich, Germany and Online

Machine Learning Conference 2025 - Hybrid Edition

### Overview
This iSAQB module SWARC4AI focuses on software architecture for AI systems. The three day program introduces how modern AI technologies can be integrated into scalable, auditable and secure software architectures. The module emphasizes data governance, MLOps, and generative AI, with a strong methodological toolkit to structure complex requirements and support sustainable architectural decisions. Participants learn how to design architectures that enable AI components such as machine learning models and generative AI to operate cohesively within broader software systems. The course blends theory with hands-on practice, ensuring attendees can translate concepts into real-world solutions that meet quality attributes like scalability, explainability, and safety.

### Target audience
The module is designed for professionals involved in software architecture, AI integration, data engineering, and related roles who want a solid foundation in architecting AI enabled systems. It is suitable for those preparing for advanced level certifications and seeking credits toward iSAQB requirements.

### Format and agenda
SWARC4AI is delivered as a structured three-day training. The agenda covers a comprehensive sequence of topics, including foundational AI concepts relevant to software architecture, differences between AI systems and traditional software, and compliance with security and privacy requirements. It includes design patterns for AI systems, integration of machine learning into existing architectures, and data management strategies such as data pipelines and data engineering tools. The program also features operating characteristics for running AI systems, including scalability, monitoring, and MLOps practices, as well as approaches to Generative AI such as LLMs and retrieval augmented generation (RAG). Real-world case studies and hands-on exercises enable participants to apply learned patterns to their own projects.

### Learning outcomes and credits
Participants will gain a structured understanding of how to design AI-enabled software architectures, focusing on scalability, security, and explainability. The module assigns credits across methodology and technology: typically 10 methodical credits and 20 technical credits, aligned with the iSAQB curriculum. Attendees will be able to articulate architectural decisions, evaluate risks, and plan for compliance with relevant regulations (e.g., EU AI Act, data privacy requirements). The course also emphasizes documentation practices for architectural decisions and the creation of artifact templates that can be reused across projects.

### Prerequisites and prerequisites alignment
Participants should have baseline knowledge in machine learning, data processing, and software architecture to maximize the benefits of the module. These prerequisites help ensure that attendees can immediately apply the concepts presented and translate them into project work.

### What you will take away
A clear understanding of how to combine AI technologies with conventional software architecture practices to create robust, scalable and auditable systems. You will learn architectural patterns for AI integration, data governance considerations, and the role of governance, security, and compliance in AI deployments. The training prepares you to design, document, and implement AI capable architectures in real-world environments and to pursue further certification within the iSAQB framework.

### FAQ
This module forms part of the Advanced Level program and offers a roadmap to further specialization in AI oriented architecture. If you need to know more about specific speakers, exact session timings, or venue logistics, please consult the event organizers for the latest schedule and details.

Modul SWARC4AI | 12 – 14 October 2026 | Munich

PHP conference in Munich, Germany and Online

AI Conferences in Munich 2026

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