Berlin DataTalksClub Group

Physics-based AI models such as neural networks, neural operators, and operator transformers - Aditya Seshaditya

We will leverage quantum machine learning techniques to enhance fluid dynamics simulations using physics-informed AI models and their quantum counterparts (Quantum PINNs). The workshop will explore various implementations, including attention-enhanced architectures. The goal is to demonstrate the potential of quantum computing in solving high-dimensional partial differential equations (PDEs) associated with fluid dynamics, improving both computational efficiency and accuracy.

Open-source frameworks: PennyLane (QML), NVIDIA PhysicsNemo (PINNs)

In this workshop, we will cover the following steps:

• Physics-inspired models
• Training and Loss-Physics
• Hybrid quantum-classical approaches

By the end of this workshop, you’ll understand the details of AI models used for simulations such as CFD (Computational Fluid Dynamics) and the relevance of physics-based approaches.

About the speaker:

Aditya Seshaditya is a Data Scientist with background in Quantum Computing, Digital Twins and AI.

Join our slack: https://datatalks.club/slack.html

​Mastering nodes, integrations, debugging, and deployment through a real-world AI content automation project — Moein Foroughi

​In this hands-on workshop, we’ll go beyond drag-and-drop demos — exploring how n8n really works under the hood, how to connect it with external APIs and databases, debug complex flows, and manage production-grade deployments.

​Along the way, we’ll build a real, functional project: an AI-assisted article writer that integrates search, scraping, and structured data storage. This project serves as a practical example to apply every key concept of n8n — from node logic and credentials management to error handling, scaling, and containerisation.

​We’ll cover the following steps:

• ​How n8n works and how to use its core nodes effectively
• ​Connecting n8n with APIs, databases, and external tools
• ​Building and troubleshooting real workflows
• ​Setting up n8n with Docker and basic deployment tips
• ​Creating a simple AI-powered SEO article writer as a hands-on project

​By the end, you’ll know how to build and run powerful n8n workflows that connect seamlessly with modern AI tools, data systems and tools.

​Level:
​Beginner to Intermediate — basic familiarity with Docker, Linux, and modern AI tools will help you get the most out of the session, but all key concepts will be introduced from first principles.
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​About the speaker:

​Moein Foroughi is a DevOps engineer focused on automation and scalable systems, with a professional interest in applying AI and modern technologies to improve engineering workflows and operational efficiency.