Edge AI Hardware Fundamentals delves into the essential components and methodologies that underpin the development and deployment of artificial intelligence at the edge of networks. Participants will engage with hands-on projects that emphasize practical applications, enabling them to design and implement AI solutions that operate efficiently on localized hardware. This course is structured to provide a comprehensive understanding of the intersection between AI algorithms and embedded systems, focusing on real-world scenarios that professionals encounter in the field.
Throughout the program, learners will explore the intricacies of hardware design, data processing, and AI model optimization for edge devices. By collaborating on projects, participants will not only gain technical expertise but also have the opportunity to contribute their findings to Cademix Magazine, fostering a culture of knowledge sharing and innovation. The course culminates in a final project that challenges participants to create a functional edge AI application, integrating the skills and concepts acquired during the training.
Introduction to Edge AI Concepts
Overview of Embedded Systems Architecture
Hardware Components for Edge AI Applications
Data Acquisition and Preprocessing Techniques
AI Model Selection and Optimization Strategies
Deployment of AI Models on Edge Devices
Real-Time Data Processing and Analytics
Power Management and Efficiency in Edge AI
Case Studies of Edge AI Implementations
Final Project: Development of an Edge AI Solution