Portable learning
publiccourseMCF 1.1

Numerical Methods and Scientific Computing 0.2.0

Published by @apv on August 12, 2026.

Source checksum
0b70c2c8ae87ca525a6d789997abb352cb87c4cb08e53601a5e4a47df3a5d9c9
Package size
518.7 KiB
Validation
valid · 0 diagnostics
Manifest ID
courses.theoria.polytechnical.numerical-methods-scientific-computing
Manifest version
0.2.0
Entry
undefined
Language
en-CA
License
CC-BY-4.0
Authors
APV, Theoria
Subjects
mathematics, numerical analysis, scientific computing, numerical linear algebra, optimization
Level
intermediate
Structure
37 lessons · 64 activities · 189 questions

Learning outcomes

  1. Reason about floating-point representation, cancellation, forward/backward error, conditioning, and algorithmic stability.
  2. Implement and verify root finding, interpolation, finite differences, quadrature, and scalar optimization methods.
  3. Solve dense and sparse linear systems with pivoting, factorization, conditioning, refinement, and iterative methods.
  4. Implement explicit ODE methods, Runge-Kutta schemes, convergence studies, and stability/stiffness diagnostics.
  5. Build reproducible scientific-computing workflows with benchmarks, tests, error budgets, and numerical/model-error separation.

Release notes

No release notes were provided.

Canonical source is immutable

This release points to the validated source `.mcf.zip`. Browser-compiled learner output is derived and is not treated as repository source.