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 Cambridge can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Cambridge
Compass House, Cambridge, united kingdom, CB24 9AD
Vision Park is within easy reach of
Cambridge city centre and has the
advantage of excellent links with the
M11 and A14.
...
Vision Park is within easy reach of
Cambridge city centre and has the
advantage of excellent links with the
M11 and A14.
Trains from London Kings Cross arrive every 30 minutes, with a 15 minute journey by taxi to the Park. Histon Railway Station is on the boundary of Vision Park, which provides high quality, frequent local transport from St Ives to Cambridge.
Guided Bus
Vision Park lies alongside the Cambridgeshire Guided Bus which offers fast and frequent buses from Histon to Huntingdon (50 minutes), St Ives (15) and Cambridge city centre (15). Onboard, there is air conditioning, free WiFi and power for your laptop and mobile devices. Please see www.thebusway.info for further information.
This instructor-led, live training in Cambridge (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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