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 training can be carried out locally on customer premises in Montpellier or in NobleProg corporate training centers in Montpellier.
NobleProg -- Your Local Training Provider
Montpellier, Garosud
NobleProg Montpellier, 48, rue Claude Balbastre, Montpellier, france, 34070
– Access Tram stop Victoire 2 Line 2 direction Saint Jean de Védas.
-Tram access then Bus take tram line 2 Sabine stop to...
– Access Tram stop Victoire 2 Line 2 direction Saint Jean de Védas.
-Tram access then Bus take tram line 2 Sabine stop towards Saint Jean de Védas then the “La Ronde” bus stop Patrice Lumumba.
- Access by car from the A9 exit 31 “Saint Jean de Védas” Montpellier Ouest, silver cross MOSSON.
-Access by train from Saint Roch station, Tram line 2 towards Saint Jean de Védas, Victory 2 stop.
– Access by plane from Montpellier airport 10 minutes by car, exit 31 of the A9 towards Barcelona or by bus from the airport line 120 to Place de l'Europe then Tram line 2 towards Saint Jean de Védas stop Victory 2
This instructor-led, live training in Montpellier (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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