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Course Outline
Introduction to Programming Big Data with R (bpdR)
- Configuring your environment for pbdR
- Exploring the scope and capabilities within pbdR
- Identifying packages frequently utilized alongside Big Data workflows in conjunction with pbdR
Message Passing Interface (MPI)
- Utilizing pbdR MPI 5
- Implementing parallel processing techniques
- Managing point-to-point communication
- Sending matrices
- Aggregating matrix sums
- Executing collective communication operations
- Summing matrices using the Reduce function
- Performing Scatter and Gather operations
- Exploring additional MPI communication methods
Distributed Matrices
- Constructing a distributed diagonal matrix
- Performing Singular Value Decomposition (SVD) on distributed matrices
- Building distributed matrices through parallel execution
Statistics Applications
- Implementing Monte Carlo Integration
- Loading datasets
- Reading data across all processes
- Broadcasting data from a single process
- Accessing partitioned data segments
- Conducting distributed regression analysis
- Executing distributed bootstrap procedures
21 Hours
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!.
