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 Ostrowiec Świętokrzyski or in NobleProg corporate training centers in Ostrowiec Świętokrzyski.
NobleProg -- Your Local Training Provider
Ostrowiec Świętokrzyski
Centrum Biurowo – Konferencyjne, Sandomierska 26A, Ostrowiec Świętokrzyski, Poland, 27-400
The training rooms are spacious, well-lit, and excellently equipped, providing comfortable conditions for ...
The training rooms are spacious, well-lit, and excellently equipped, providing comfortable conditions for participants. Additionally, the building features a ramp and an elevator, facilitating access for individuals with limited mobility and easing the transportation of training equipment. The facility is located just 3.5 kilometers from the city center, allowing for quick and easy access to other urban attractions. Moreover, it is only 600 meters away from the nearest bus stop, making it convenient for participants using public transportation.
This instructor-led, live training in Ostrowiec Świętokrzyski (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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