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Numerical linear algebra · Graduate · Math

Topics

Large-scale and applied problems

  • Sparse matrix formats and memory-aware implementations
  • Parallel and distributed linear algebra (overview)
  • Least squares and ridge regression at scale
  • Randomized numerical linear algebra (sketching, introduction)
  • Applications in data science, imaging, and PDE discretizations

Software and practice

  • LAPACK/BLAS ecosystem and best practices
  • Conditioning diagnostics in engineering workflows
  • Mixed-precision algorithms (introduction)
  • Benchmarking and reproducibility in HPC environments
  • Case studies from structural analysis and machine learning

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$1,162 · Numerical linear algebra · 18 tutoring hrs

Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle or Venmo.