Local, instructor-led live GPU (Graphics Processing Unit) training courses demonstrate through interactive discussion and hands-on practice the fundamentals of GPU and how to program GPUs.
GPU training is available as "onsite live training" or "remote live training". Onsite live GPU training can be carried out locally on customer premises in Norge or in NobleProg corporate training centers in Norge. Remote live training is carried out by way of an interactive, remote desktop.
NobleProg -- Your Local Training Provider
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Testimonials
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Kurs: Inkscape
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Kurs: Adobe LiveCycle Designer
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Kurs: Adobe Illustrator
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Kurs: Adobe Illustrator
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Kurs: Adobe LiveCycle Designer
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Kurs: Techniki graficzne (Adobe Photoshop, Adobe Illustrator)
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GPU (Graphics Processing Unit) Underkategorier
Graphics Processing Unit (GPU) Kursplaner
Kursnavn
Varighet
Oversikt
Kursnavn
Varighet
Oversikt
14 timer
Oversikt
Dette kurset dekker hvordan du programmerer GPU er for parallell databehandling. Noen av applikasjonene inkluderer dyp lærings-, analyser- og ingeniørapplikasjoner.
14 timer
Oversikt
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 timer
Oversikt
Dette instruktørledede, liveopplæringsløpet dekker hvordan du programmerer GPU er for parallell databehandling, hvordan du bruker forskjellige plattformer, hvordan du jobber med CUDA-plattformen og dens funksjoner, og hvordan du utfører forskjellige optimaliseringsteknikker ved bruk av CUDA. Noen av applikasjonene inkluderer dyp læring, analyse, bildebehandling og tekniske applikasjoner.
14 timer
Oversikt
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.
Kommende Graphics Processing Unit (GPU) Kurs
2020-11-17 09:30:00
14 timer
2020-12-17 09:30:00
14 timer
2021-01-07 09:30:00
14 timer
2021-02-09 09:30:00
14 timer
2021-03-31 09:30:00
14 timer
Rådgivning
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