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. Guatemala City onsite live RAPIDS trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Guatemala - Europlaza
5a Avenue 5-55 Zone 14, Guatemala City, Guatemala, 1014
The Guatemala Europlaza Center is located on the second floor of one of the four modern 19-story towers that form the Europlaza World Business Center. The Guatemala Europlaza Center is convenient for public transport connections, including the new Transmetro bus system introduced to improve traffic flow, and the city Center is just 10 minutes away.
Guatemala - Citibank Tower
3r avenue 13-78, zone 10 , Guatemala City, Guatemala, 01010
Experience convenient access to Citibank Tower via public transportation or by car, with on-site parking available. Additionally, relish seamless international travel with the airport a mere 15-minute drive from the tower.
This instructor-led, live training in Guatemala City (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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