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Grades: 176
Median GPA: A
Mean GPA: 3.941
3.1
Professor rating
1.6
Difficulty
17
Ratings given
100%
Would take again
Scientific Computing
PHYS 5315
School of Natural Sciences and Mathematics
An introduction to computational methods for: Machine precision, truncation, and rounding errors. Linear algebra, Gauss-Jordan Elimination, LU Decomposition, Singular Value Decomposition. Least squares fitting, linear, polynomial. Interpolation, cubic spline, rational function. Integration. Special functions. Sorting and Selection. Root Finding and Nonlinear Sets of Equations. Random numbers. Monte Carlo Methods. Optimization, minimization or maximization, random searching, hill climbing, simulated annealing, genetic algorithms. Eigensystems. Fourier methods. Wavelets. ODEs and PDEs. Brief introduction to machine learning. 3 credit hours.
Prerequisite or Corequisite: PHYS 5301.
Offering Frequency: Each year
Grades: 81
Median GPA: A
Mean GPA: 3.955
Click a checkbox to add something to compare.
Grades: 176
Median GPA: A
Mean GPA: 3.941
3.1
Professor rating
1.6
Difficulty
17
Ratings given
100%
Would take again
Scientific Computing
PHYS 5315
School of Natural Sciences and Mathematics
An introduction to computational methods for: Machine precision, truncation, and rounding errors. Linear algebra, Gauss-Jordan Elimination, LU Decomposition, Singular Value Decomposition. Least squares fitting, linear, polynomial. Interpolation, cubic spline, rational function. Integration. Special functions. Sorting and Selection. Root Finding and Nonlinear Sets of Equations. Random numbers. Monte Carlo Methods. Optimization, minimization or maximization, random searching, hill climbing, simulated annealing, genetic algorithms. Eigensystems. Fourier methods. Wavelets. ODEs and PDEs. Brief introduction to machine learning. 3 credit hours.
Prerequisite or Corequisite: PHYS 5301.
Offering Frequency: Each year
Grades: 81
Median GPA: A
Mean GPA: 3.955
Click a checkbox to add something to compare.
