EDGE AI FOUNDATION Courses

High-Efficiency Embedded Computer Vision for TinyML

Explore advanced computer vision capabilities on microcontrollers, from face landmark detection to pose detection, using energy-efficient NPU integration for endpoint deployment.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Making ML Tiny with High-Level Synthesis - Optimizing AI Accelerators

Discover how High-Level Synthesis enables optimal ML accelerator design for ASIC/FPGA, exploring quantization, caching strategies, and efficient implementation techniques for Edge and IoT systems.

• YouTube
• 1 hour
• On-Demand
• Free Video

Embedded Edge Intelligence with Infineon Products and Imagimob Studio

Discover how to develop ML-based edge devices using Infineon's PSOC™ Edge MCUs and Imagimob Studio platform for efficient AI deployment and low-power operation.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Unleashing the Power of Tiny Neural Network Models in Medical Devices

Explore how tinyML and neural networks are revolutionizing medical devices through advanced diagnostic capabilities, personalized monitoring, and efficient on-edge performance optimization.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Streamlining TinyML Application Development Using Open-CMSIS and Visual Studio Code

Discover how to streamline machine learning development for embedded systems using Arm CMSIS extensions in VSCode, from application creation to deployment on various platforms.

• YouTube
• 56 minutes
• On-Demand
• Free Video

MicroCam - A Low-Power and Privacy Preserving Multi-modal Sensor Platform for Occupancy Detection

Discover how MicroCam's innovative multi-modal sensor platform uses AI and IoT technology to detect residential occupancy, enabling energy-efficient HVAC control while maintaining privacy and operating on battery power.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Architecture 2.0: Prompt Engineering and Foundation Models for Edge AI Hardware Design

Explore how foundation models and generative AI revolutionize TinyML hardware design through prompt engineering, enabling efficient edge AI solutions and accelerated development cycles.

• YouTube
• 23 minutes
• On-Demand
• Free Video

On-Device Generative AI: Deployment, Optimization, and Advanced Techniques

Discover how on-device AI deployment transforms computing through advanced optimization techniques, from model distillation to speculative decoding, enabling efficient generative AI processing across devices.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Foundation Model for Efficient Natural Disaster Damage Assessment Using Multi-Modal Data

Discover how AI and UAV technology combine with multimodal data to revolutionize natural disaster damage assessment, enabling faster emergency response through innovative deep learning solutions.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Using Generative Models to Improve Generative Models - Data-Centric Efficient AI

Discover how combining multiple generative models can create sophisticated data, enhance AI capabilities, and address data scarcity challenges in edge AI applications through strategic model integration.

• YouTube
• 20 minutes
• On-Demand
• Free Video

MobileLLM - Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Discover how MobileLLM optimizes language models for mobile devices through innovative architecture design, achieving superior performance with fewer parameters and reduced computational costs.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Unlocking New Frontiers in Wearable Technology with TinyML

Explore how TinyML enables advanced wearable technology development, focusing on ultra-low power systems, biosensor integration, and real-world applications in smart rings and health monitoring.

• YouTube
• 51 minutes
• On-Demand
• Free Video

Visual Language Models for Edge AI 2.0 - Multi-image Reasoning and In-context Learning

Explore cutting-edge innovations in visual language models, focusing on VILA's multi-image reasoning capabilities, AWQ quantization, and efficient edge AI deployment strategies.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Physics-Aware Auto Tiny Machine Learning for Edge Devices

Explore physics-aware neurosymbolic AI optimization for resource-constrained devices, combining symbolic techniques with machine learning for enhanced edge computing applications.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Building a Music Genre Recognition Application with TinyML on Raspberry Pi Pico

Discover how to build a music genre recognition system on Raspberry Pi Pico using TensorFlow Lite and CMSIS-DSP, from feature extraction to ML model deployment with LSTM neural networks.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video