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. Lima onsite live RAPIDS trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Lima - Edificio Tempus San Isidro
Av. Santo Toribio 115, Lima, peru, 27
Edificio Tempus is a Class A brand new office building is strategically located in the corner of Av Victor Belaunde and Av. San Toribio in the heart of San Isidro. There is plenty of parking on 4 parking decks. This center is only a short 300 mt walk in the same block from our exiting Real Seis in located in Centro Empresarial.
Lima - Miguel Grau
Av. Almte. Miguel Grau 709 Lima , Lima, Peru, 15063
Expand your business horizons with a workspace in Barranco, one of Lima's 43 districts, boasting excellent connectivity to its surroundings. Enjoy effortless commuting to your office via the Avenida Almirante Miguel Grau S/N and Bulevar - Embarque Sur 2 bus stops.
This instructor-led, live training in Lima (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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