本地，講師指導的現場GPU（圖形處理單元）培訓課程通過交互式討論和動手實踐演示了GPU的基本原理以及如何編程GPU。 GPU培訓可用作“現場實時培訓”或“遠程實時培訓”。現場培訓可以在當地的客戶場所進行台灣或者在NobleProg的企業培訓中心台灣 。遠程實時培訓通過交互式遠程桌面進行。 NobleProg - 您當地的培訓機構
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客戶評論
例子討論了生活，偏離，"生活"的例子。一種培訓形式，即將講座與實際示例相互交聯，並討論這些示例。
Piotr Glazor - Nokia
課程: NVIDIA GPU Programming - Extended
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所有
Dominik Kutten
課程: Adobe LiveCycle Designer
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班級組織Jaro
Jarosław Jasiński
課程: Adobe Illustrator
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知識和對問題的反應
Tadeusz Kopryaniuk
課程: Adobe Illustrator
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培訓師真正針對我們對一個非常具體的案例研究的需求，並且能夠適應形勢（作為我們在課程中形成的問題的解決方案），超越了他所做的上游準備。
Anne-Sophie Schwindenhammer
課程: Inkscape
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一切。
Janusz Magnuszewski - mLeasing
課程: Adobe LiveCycle Designer
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研究實例
Kacper Gardziała - Exacto Sp. z o.o.
課程: Adobe Illustrator
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專注于受訓者的需求
Barbara Szubert-Tabaczka - Volkswagen Poznań Sp. z o.o.
課程: Adobe LiveCycle Designer
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知識和它的溝通方式。
Magdalena Rokoszewska - Agencja Kreatywna Przereklamowani
課程: Techniki graficzne (Adobe Photoshop, Adobe Illustrator)
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練習
Intel Technology Poland SP. z o.o.
課程: Inkscape
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演示者的知識,主題,訪問門戶與練習,是課程被記錄,我可以聽它一段時間。
Intel Technology Poland SP. z o.o.
課程: Inkscape
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Graphics Processing Unit (GPU)子類別
Graphics Processing Unit課程大綱
課程名稱
課程時長
概觀
課程名稱
課程時長
概觀
14小時
概觀
CUDA (Compute Unified Device Architecture) is a parallel computing platform and API created by Nvidia.
This instructor-led, live training (online or onsite) is aimed at developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.
By the end of this training, participants will be able to:
- Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
- Create, compile and launch custom CUDA kernels.
- Manage GPU memory.
- Convert a CPU based application into a GPU-accelerated application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (online or onsite) is aimed at developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.
By the end of this training, participants will be able to:
- Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
- Create, compile and launch custom CUDA kernels.
- Manage GPU memory.
- Convert a CPU based application into a GPU-accelerated application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
21小時
概觀
這個講師主導的現場培訓課程包括如何為並行計算編程GPU ，如何使用各種平台，如何使用CUDA平台及其功能，以及如何使用CUDA執行各種優化技術。一些應用程序包括深度學習，分析，圖像處理和工程應用程序。
14小時
概觀
Video analytics refers to the technology and techniques used to process a video stream. A common application would be capturing and identifying live video events through motion detection, facial recognition, crowd and vehicle counting, etc.
This instructor-led, live training (online or onsite) is aimed at developers who wish to build hardware-accelerated object detection and tracking models to analyze streaming video data.
By the end of this training, participants will be able to:
- Install and configure the necessary development environment, software and libraries to begin developing.
- Build, train, and deploy deep learning models to analyze live video feeds.
- Identify, track, segment and predict different objects within video frames.
- Optimize object detection and tracking models.
- Deploy an intelligent video analytics (IVA) application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (online or onsite) is aimed at developers who wish to build hardware-accelerated object detection and tracking models to analyze streaming video data.
By the end of this training, participants will be able to:
- Install and configure the necessary development environment, software and libraries to begin developing.
- Build, train, and deploy deep learning models to analyze live video feeds.
- Identify, track, segment and predict different objects within video frames.
- Optimize object detection and tracking models.
- Deploy an intelligent video analytics (IVA) application.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
近期GPU培訓課程
2021-02-08 09:30:00
14 時間：
2021-02-10 09:30:00
14 時間：
2021-02-10 09:30:00
14 時間：
2021-02-15 09:30:00
21 時間：
2021-03-29 09:30:00
14 時間：
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