GPU Training Courses

GPU Training Courses

Οι τοπικές εκπαιδευτικές σειρές μαθημάτων GPU (Graphics Processing Unit) με επίκεντρο το μάθημα του καθηγητή, επιδεικνύουν μέσω της διαλογικής συζήτησης και της πρακτικής άσκησης τις βασικές αρχές της GPU και τον προγραμματισμό των GPU. Η εκπαίδευση GPU είναι διαθέσιμη ως "onsite live training" ή "remote live training". Η επιτόπια κατάρτιση σε πραγματικό χρόνο μπορεί να πραγματοποιηθεί σε τοπικό επίπεδο στις εγκαταστάσεις του πελάτη Ελλάδα ή σε εταιρικά κέντρα κατάρτισης NobleProg στο Ελλάδα . Η απομακρυσμένη ζωντανή προπόνηση πραγματοποιείται μέσω μιας διαδραστικής, απομακρυσμένης επιφάνειας εργασίας. NobleProg - Ο τοπικός παροχέας εκπαίδευσης

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GPU (Graphics Processing Unit) Subcategories

GPU Course Outlines

Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
Overview
Αυτό το μάθημα καλύπτει τον τρόπο προγραμματισμού των GPU για παράλληλους υπολογιστές. Ορισμένες από τις εφαρμογές περιλαμβάνουν εφαρμογές βαθιάς μάθησης, ανάλυσης και μηχανικής.
21 hours
Overview
This instructor-led, live training course in Ελλάδα 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
Overview
This instructor-led, live training in Ελλάδα (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.
14 hours
Overview
This instructor-led, live training in Ελλάδα (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.

Upcoming GPU (Graphics Processing Unit) Courses

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As a NobleProg Trainer you will be responsible for:

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