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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-on-device-ai/
课程评论：没有评论
课程名称：构建设备端AI 课程概述：如果您是开发者、数据科学家，或者对人工智能有兴趣的爱好者，并且希望为边缘设备创建可部署的高效AI模型，那么本课程正适合您。您想加速AI推理并减少计算开销吗？您是否在寻找优化移动设备、物联网（IoT）和嵌入式系统模型的实用技术？本课程将教您如何训练、编译、分析和优化AI模型，确保它们在资源受限的设备上高效运行而不妥协性能。 在本课程中，您将： 1. 学习设备端AI部署的完整工作流程—从训练到推理。 2. 了解高通AI中心及其在AI模型管理中的使用。 3. 探索模型编译和分析以提升性能。 4. 实施推理技术以在边缘设备上部署模型。 5. 掌握量化技术，优化AI模型以适应低功耗硬件。 学习设备端AI的意义：在边缘设备上部署AI可以减少延迟、增强隐私，并优化性能而不依赖于云计算。通过掌握量化、模型分析与高效的AI部署，您可以保证模型运行更快、功耗更少，且准备好应用于移动AI、自动系统和IoT等现实世界场景。 通过本课程，您将获得处理实际AI部署场景的动手经验。您将理论与实践相结合，使您的模型更精简、更智能、并准备好投入使用。 在课程结束时，您将掌握训练、优化和部署AI模型在边缘设备上的技能，成为AI部署领域的宝贵资产。 准备好提升您的AI模型水平了吗？现在就报名，开始您的学习之旅吧！
If you are a developer, data scientist, or AI enthusiast looking to create deployment-ready efficient AI models for edge devices, this course is for you. Do you want to accelerate AI inference while reducing computational overhead? Are you looking for practical techniques to optimize your models for mobile, IoT, and embedded systems?This course will teach you how to train, compile, profile, and optimize AI models, ensuring they run efficiently on resource-constrained devices without compromising performance.In this course, you will:1. Learn the complete workflow of On-Device AI Deployment - from training to inference.2. Understand Qualcomm AI Hub and how to use it for AI model management.3. Explore model compilation and profiling to enhance performance.4. Implement inference techniques for deploying models on edge devices.5. Master quantization techniques to optimize AI models for low-power hardware.Why Learn On-Device AI?Deploying AI on edge devices allows you to reduce latency, enhance privacy, and optimize performance without depending on cloud computing. By mastering quantization, model profiling, and efficient AI deployment, you can ensure your models run faster, consume less power, and are ready for real-world applications like mobile AI, autonomous systems, and IoT.Throughout the course, you'll gain hands-on experience with real-world AI deployment scenarios. You will balance theory and practical application to make your models leaner, smarter, and deployment-ready.By the end of the course, you'll be equipped with the skills to train, optimize, and deploy AI models on edge devices, making you a valuable asset in the field of AI deployment.Ready to take your AI models to the next level? Enroll now and start your journey!
