Embedded AI with Raspberry Pi focuses on the integration of artificial intelligence within embedded systems, specifically utilizing Raspberry Pi as a platform. Participants will engage in a hands-on, project-based learning environment where they will develop practical skills in deploying AI algorithms and machine learning models on embedded devices. This approach not only enhances technical proficiency but also prepares participants to tackle real-world challenges in various industries.
Throughout the course, learners will explore the capabilities of Raspberry Pi in conjunction with AI technologies. They will work on projects that involve data collection, model training, and implementation, culminating in a final project that showcases their understanding and application of embedded AI. By encouraging participants to publish their results in Cademix Magazine, the course promotes knowledge sharing and professional visibility within the tech community.
Introduction to Raspberry Pi and its ecosystem
Overview of AI concepts and machine learning fundamentals
Setting up the Raspberry Pi for AI applications
Data collection and preprocessing techniques
Implementing machine learning algorithms on Raspberry Pi
Using TensorFlow Lite for model deployment
Real-time data processing and analysis
Project management and documentation best practices
Final project: Developing an AI-driven application using Raspberry Pi
Presentation and publication of project results in Cademix Magazine