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. Utrecht onsite live RAPIDS trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Utrecht
The Office Operators, Stadsplateau 7, Utrecht, Netherlands, 3521 AZ
Training courses in the very heart of Utrecht city centre, with Central Station at your doorstep. NobleProg has the use of 16...
Training courses in the very heart of Utrecht city centre, with Central Station at your doorstep. NobleProg has the use of 16 professional and modern training rooms in the Utrecht WTC Meeting & Conference center.
All rooms are equipped with LCD screens and every room offers natural day light.
The WTC Utrecht is located directly adjacent to Utrecht Central Station, within walking distance from the historical centre and has ample parking opportunities for cars as well as bicycles. This makes WTC Utrecht a dream location for organisations that are looking for the ideal place to hold their meetings.
This instructor-led, live training in Utrecht (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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Testimonials (2)
examples and exercises
Kamil
Course - Introduction to Data Science and AI using Python
Machine Translated
From learning, being able to put the proposed exercises into practice.
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