Databases and Computational Tools Used in Big Data

Catalog description

Credits 3. 3 Lecture Hours. Survey of common tools used by statisticians for high performance computing and big data type problems; shell scripting; HPC clusters; code optimization and vectorization; parallelizing applications using numerical libraries; open MP, MPI and parallel R; data management and revision control using Git; exploration of SQL, survey NOSQL databases; introduction to Python. Prerequisites: Knowledge of R, Fortran, or C.