AI Products with Domain-driven Design

2024-10-22 - 2024-10-23

AI Products with Domain-driven Design (Online) - German


Are you up to the challenge of developing innovative data-driven software solutions? Do you wonder where AI can be used in product development? Nowadays, there are countless models available through APIs and open-source solutions that can be used without having to train your own model. It’s all there. Commodity AI is possible. How do you get started? Where in your product makes sense to integrate AI? What features are now possible that weren’t achievable or too expensive before?

If this speaks to you, then this training is for you! Let our experienced trainers introduce you to the practical application of Artificial Intelligence and Machine Learning. Learn how to identify and validate AI/ML use cases, and gain an in-depth understanding of the right tools and strategies for successful implementation and deployment. Throughout the workshop, we use the Domain-driven Design methodology, which requires no prior knowledge.

Dr. Larysa Visengeriyeva during a workshop break in exchange with participants

Day 1: In the first practical part, we will learn about Event Storming and the ML Design Canvas. Event Storming is a method of Collaborative Modeling and Knowledge Crunching, a methodology of Domain-Driven Design. It helps domain experts, technical experts, developers and all other team members to develop a common understanding of the business domain. In doing so, we start from use cases examples, and so we can then identify further use cases in a project for innovative AI/ML technologies. Prior Domain-Driven Design knowledge is not necessary.

**Day 2: In the second practical part, we formulate concrete ML problems together, based on the use cases we have found. We do this on the ML Design Canvas, which was introduced on the first day. Afterwards, we structure the ML project on the canvas and specify all components for the training and prediction phases. Then we discuss the Data Landscape Canvas to clarify the data availability as last step.

Your Trainers

Dr. Larysa Visengeriyeva


Machine Learning and MLOps

Larysa is a senior consultant with INNOQ in Berlin. She received her doctorate in Augmented Data Quality Management at the TU Berlin. At INNOQ she is working on the operationalization of Machine Learning (MLOps). She’s the author of

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