Faculty of Artificial intelligence

Faculty of Artificial intelligence

Embedded AI Systems: Bridging Intelligence and Hardware.

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  • This course is meticulously designed to equip IT students with a powerful blend of theoretical knowledge and practical skills in the dynamic field of Embedded Artificial Intelligence.

    • Foundational Mastery: You'll gain a solid understanding of both embedded systems (microcontrollers, sensors, actuators, and their limitations) and the core concepts of Artificial Intelligence, Machine Learning, and Deep Learning. This includes distinguishing between edge and cloud AI paradigms.

    • Hardware Expertise: Develop skills in selecting and optimizing hardware for AI applications, including traditional MCUs and specialized AI accelerators like NPUs, TPUs, and FPGAs. Learn about sensor integration and memory management, crucial for resource-constrained environments.

    • Software Proficiency: Dive into TinyML frameworks (TensorFlow Lite Micro, Edge Impulse) and master embedded C/C++ programming for AI. You'll learn to optimize code for optimal performance and memory usage, and effectively deploy pre-trained models on edge devices.

    6h
    0
    15
Free
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