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 Antwerp can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Antwerp
Hotel NH Collection Antwerp Centre, Pelikaanstraat 84, 2018 Antwerpen, Belgium, Antwerp, Belgium, 2018
The hotel has a conference capacity for up to 110 attendees, with 6 dedicated, flexible spaces available. A range of smaller...
The hotel has a conference capacity for up to 110 attendees, with 6 dedicated, flexible spaces available. A range of smaller boardrooms and a larger conference room is available for large and small meetings. The facilities include up-to-date audio-visual equipment, with refreshments available to order and an events planner on site for assistance. Unusually for a city center hotel, the hotel offers parking in its own garage.
This instructor-led, live training in Antwerp (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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