Explore how to accelerate embedded DSP and ML and edge AI application development using the Synchronous Data Stream (SDS) Framework in Keil Studio. This session will guide you through deploying SDS-based templates to hardware, collecting and labeling data from real sensors, and integrating these workflows into your machine learning pipeline.
You’ll also learn how SDS enables low-cost simulation and continuous testing for streamlined development.
Time: 8 a.m. PDT | 4 p.m. BST | 5 p.m. CET and on-demand
Length: 30 min with live Q&A
What You Will Learn:
- How to set up the SDS Framework in Keil Studio.
- How to collect and stream real-time sensor data from embedded targets.
- How to efficiently label and organize datasets for ML training.
- How to integrate data collection with your ML toolchain.
- How to accelerate development using simulation and cloud-based CI/MLOps pipelines.
Who Should Attend:
Embedded developers, ML engineers, and system designers who are building DSP or AI-enabled devices and need to streamline the path from sensor data acquisition to model deployment.
This webinar is part of "The Keil Studio" series. Unlock new levels of productivity in embedded systems design with Keil Studio—the modern Arm IDE built on Visual Studio Code. This webinar series walks you through project setup, STM32 integration, ML application development, and real-time data streaming—all within one unified development environment.