AI on the Edge: Practical Implementation with ESP32

1. Participants will be able to design, develop, and deploy AI models for specific applications on ESP32 microcontrollers. 2. Participants will gain proficiency in data acquisition, preprocessing, and feature engineering for effective model training. 3. Participants will demonstrate the ability to optimize AI models for resource-constrained environments and achieve real-time performance on ESP32.

Module 1: Foundations: Understand AI, ML, and ESP32 basics. Set up development environment. Module 2: Data Handling: Collect, preprocess, and prepare data for ML model development. Module 3: ML Model Development: Learn ML algorithms, model training, and optimization. Module 4: Deployment: Convert and deploy ML models onto ESP32 for real-time inference. Module 5: Practical Application: Build AI projects using ESP32 and explore real-world use cases.