Python is the de facto standard for machine learning. But Kotlin also offers interesting possibilities in this area. By combining both languages in a mixed architecture, you can get the best out of both worlds. The talk presents a mixed architecture of Kotlin and Python including the required frameworks for three exemplary areas of the machine learning lifecycle: data exploration in Jupyter, model architectures and model serving. The goal is to get the best out of both worlds! Let's become data science experts!