Content

  • Elementary data types and the connection to mathematics
  • Scientific data types: Multidimensional arrays, sparse arrays, data frames, missing data
  • Multiple Dispatch as an efficient paradigm for scientific programming
  • Literate Programming
  • Profiling and Benchmarks
  • Acceleration techniques: caching, multi-threading, SIMD, GPGPU
  • Scientific Data Formats: CSV, TOML, HDF5, and selected examples
  • Data visualization
  • Standard numerical techniques and efficient program libraries (BLAS, LAPACK, FFTW, ...)
  • Tests, code management, documentation
  • Reproducible science