Online or onsite, instructor-led live RAPIDS training courses demonstrate through interactive hands-on practice how to use RAPIDS to build GPU-accelerated data pipelines, workflows, and visualizations, applying machine learning algorithms, such as XGBoost, cuML, etc.
RAPIDS training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live RAPIDS trainings in Grenoble can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Grenoble, Centre Ville Proche Gare
NobleProg Grenoble, 34 avenue Felix Viallet, Grenoble, france, 38000
Training courses can be organised at our premises in Grenoble, at your premises, or remotely.
Training courses are given in...
Training courses can be organised at our premises in Grenoble, at your premises, or remotely.
Training courses are given in English or French. We organise a coordination meeting with the trainer and the participants to adapt the training program to your expectations. The courses consist of interactive discussions, theoretical parts and practical exercises.
The training is available as "live on-site training" or "live remote training". Live on-site training can be conducted locally at the client's premises in Grenoble or at the NobleProg corporate training centers in Grenoble.
Remote e-learning is conducted using an interactive desktop computer. NobleProg is the publisher of the DaDesktop software, which is presented in a video at https://www.dadesktop.com/
This instructor-led, live training in Grenoble (online or onsite) is aimed at data scientists and developers who wish to use RAPIDS to build GPU-accelerated data pipelines, workflows, and visualizations, applying machine learning algorithms, such as XGBoost, cuML, etc.
By the end of this training, participants will be able to:
Set up the necessary development environment to build data models with NVIDIA RAPIDS.
Understand the features, components, and advantages of RAPIDS.
Leverage GPUs to accelerate end-to-end data and analytics pipelines.
Implement GPU-accelerated data preparation and ETL with cuDF and Apache Arrow.
Learn how to perform machine learning tasks with XGBoost and cuML algorithms.
Build data visualizations and execute graph analysis with cuXfilter and cuGraph.
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