You are faced with the task of developing innovative, data-driven software products and have already gained some practical experience with machine learning. Now the question arises: Which problem area(s) can be addressed in product development with ML?
Sounds familiar? Then this workshop is just right for you! Learn from our trainers how to find and verify AI/ML use cases and get the right tools and procedures for product finalization. We use effective DDD methodology (no previous DDD knowledge necessary).
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.