GPU-accelerated data analysis with NVIDIA RAPIDS
The training introduces participants to the world of high-performance data analysis using the NVIDIA RAPIDS platform. The program focuses on the practical use of GPU acceleration to process and analyze large data sets. Participants, through hands-on workshops, learn to implement high-performance analytics solutions using the computing power of graphics cards.
Issues
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NVIDIA RAPIDS
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GPU acceleration
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Data processing
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Machine learning
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Performance optimization
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Memory management
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Scaling up solutions
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Integration of systems
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Performance monitoring
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Debugging
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Best practices
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Implementing solutions
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Practical applications
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Analysis of experimental data
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Reporting of results
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Automation of analysis
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Reproducible research
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R environment
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Statistical analysis
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Data visualization
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Statistical tests
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Regression and modeling
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Analysis of variance
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Reporting of results
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Automation of analysis
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Reproducibility of research
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Analysis packages
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Interactive charts
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Publication of results
Benefits
- The participant will gain practical skills in using GPU to accelerate data analysis
- Will learn to implement efficient analytical solutions using RAPIDS
- Will develop the ability to optimize the processing of large data sets
- Will learn techniques for efficient use of GPU resources in data analysis
- Will be able to integrate RAPIDS with existing analytical solutions
- Will master methods for scaling and monitoring the performance of GPU-based solutions.The participant will gain practical skills in using R in scientific data analysis
- He or she will learn to perform advanced statistical analysis and interpret the results
- Will develop the ability to create professional visualizations of research data
- Methods for automating the data analysis process
- Will be able to prepare reproducible research reports
- Will master techniques for working effectively with large data sets in the R environment
Who is this training for?
Prerequisites
- Knowledge of Python language
- Experience in data analysis
- Fundamentals of ML algorithms
- Familiarity with analytics platforms
- Basic knowledge of statistics
- Experience in working with data
- The ability to think logically
- Knowledge of research methods
Training program
Platform architecture
- Components of the ecosystem
- Installation and configuration
- Integration with Python
GPU processing
- Operations on data frames
- Transformations and aggregations
- Streaming operations
Memory optimization
- Machine learning on the GPU
- ML algorithms in RAPIDS
Training models
- Inference
- Performance optimization
- Integration and implementation
- Integration into the ecosystem
- Scaling up solutions
- Performance monitoring
Delivery Methods
Online
- Convenience of participating from anywhere
- Interactive live sessions with trainer
- Materials available for 30 days
- No travel costs
On-site
- Direct contact with trainer and group
- Intensive hands-on workshops
- Networking with other participants
- Full focus on learning
Frequently asked questions
Who is the GPU-accelerated data analysis with NVIDIA RAPIDS training for?
This training is designed for professionals looking to develop skills in gpu-accelerated data analysis with nvidia rapids. Required level: advanced.
How long is the GPU-accelerated data analysis with NVIDIA RAPIDS training?
The training lasts 2. Available in online or on-site format.
Will I receive a certificate?
Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.
Can this training be conducted for a closed group?
Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.
Request a quote
Funding Options
Check funding options for your company
Development Services Database
Up to 80% funding for SMEs from EU funds
Check availabilityNational Training Fund
Up to 100% funding for employers
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