Local instructor-led live GPU training courses in България.
Oтзиви от потребители
The trainer really targeted our need to a very specific case study and was able to adapt to the situation (as the solutions to our problematic evolved during the course), beyond the upstream preparation he did.
Anne-Sophie Schwindenhammer
Course: Inkscape
All
Dominik Kutten
Course: Adobe LiveCycle Designer
organization of classes
Jarosław Jasiński
Course: Adobe Illustrator
knowledge and reactivity to problems
Tadeusz Kopryaniuk
Course: Adobe Illustrator
all.
Janusz Magnuszewski - mLeasing
Course: Adobe LiveCycle Designer
work on examples
Kacper Gardziała - Exacto Sp. z o.o.
Course: Adobe Illustrator
Concentrating on the needs of the trained
Barbara Szubert-Tabaczka - Volkswagen Poznań Sp. z o.o.
Course: Adobe LiveCycle Designer
Knowledge and the way it is communicated.
Magdalena Rokoszewska - Agencja Kreatywna Przereklamowani
Course: Techniki graficzne (Adobe Photoshop, Adobe Illustrator)
Упражнения
Intel Technology Poland SP. z o.o.
Course: Inkscape
Machine Translated
Познаването на презентатора, предмета, достъпа до портала с упражнения е, че курсът е записан и аз мога да го изслушам за известно време.
Intel Technology Poland SP. z o.o.
Course: Inkscape
Machine Translated
GPU Subcategories
GPU Course Outlines
Име на Kурса
Продължителност
Общ преглед
Име на Kурса
Продължителност
Общ преглед
14 hours
Общ преглед
This course covers how to program GPUs for parallel computing. Some of the applications include deep learning, analytics, and engineering applications.
14 hours
Общ преглед
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 hours
Общ преглед
This instructor-led, live training course covers how to program GPUs for parallel computing, how to use various platforms, how to work with the CUDA platform and its features, and how to perform various optimization techniques using CUDA. Some of the applications include deep learning, analytics, image processing and engineering applications.
14 hours
Общ преглед
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.
Upcoming GPU Courses
2020-11-24 09:30:00
14 hours
2020-12-02 09:30:00
14 hours
2021-01-14 09:30:00
14 hours
2021-01-25 09:30:00
14 hours
2021-03-08 09:30:00
14 hours
Other countries
Consulting
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