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Duration 21 hours
Course Outline
Introduction to Big Data Programming with R (bpdR)
- Configuring your environment to utilize pbdR
- Understanding the scope and available tools within pbdR
- Identifying common packages used alongside pbdR for Big Data tasks
Message Passing Interface (MPI)
- Implementing pbdR MPI 5
- Executing parallel processing tasks
- Managing point-to-point communication
- Transmitting Matrices
- Aggregating Matrix Sums
- Utilizing collective communication
- Summing Matrices using the Reduce function
- Applying Scatter and Gather operations
- Exploring other MPI communication methods
Distributed Matrices
- Generating a distributed diagonal matrix
- Performing Singular Value Decomposition (SVD) on a distributed matrix
- Constructing a distributed matrix in parallel
Statistical Applications
- Applying Monte Carlo Integration
- Ingesting Datasets
- Reading data across all processes
- Broadcasting information from a single process
- Processing partitioned data
- Conducting Distributed Regression
- Implementing Distributed Bootstrap
Testimonials (2)
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
