STEM / applied
Computational physics · Undergraduate · Physics
Learning objectives from the Computational physics syllabus, grouped by unit. Click an objective for study materials.
Learning objectives
Click an objective for study materials.
Numerical foundations
- Floating-point arithmetic and stability — Floating-point arithmetic and stability
- Root finding and linear algebra routines — Root finding and linear algebra routines
- Numerical differentiation and integration — Numerical differentiation and integration
- ODE solvers: Euler, RK4, and adaptive step — ODE solvers: Euler, RK4, and adaptive step
- Interpolation and least-squares fitting — Interpolation and least-squares fitting
Simulation methods
- Molecular dynamics for particle systems — Molecular dynamics for particle systems
- Monte Carlo integration and sampling — Monte Carlo integration and sampling
- Finite-difference PDEs: heat and wave equations — Finite-difference PDEs: heat and wave equations
- Eigenvalue problems for quantum wells — Eigenvalue problems for quantum wells
- Chaos in logistic and driven oscillators — Chaos in logistic and driven oscillators
Data and visualization
- Python/NumPy/Matplotlib workflows — Python/NumPy/Matplotlib workflows
- Error bars and bootstrap resampling — Error bars and bootstrap resampling
- Animating time evolution of fields — Animating time evolution of fields
- Version control for scientific code — Version control for scientific code
- Reproducibility and random seeds — Reproducibility and random seeds
What each unit includes
Open a unit below for full materials. Typical resources:
- Study guide
- Exam Strategy
- Common Mistakes
- Worksheets
- Word problems
- Mixed Practice
- Multi-Unit Problems
- Review
- Practice test
- Answer key
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Numerical foundations
Floating-point arithmetic and stability
Coming soon - Simulation methods
Molecular dynamics for particle systems
Coming soon - Data and visualization
Python/NumPy/Matplotlib workflows
Coming soon
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$1,162 · Computational physics · 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.