|  |  |  |  |  |  |  |  |  |  | 
		
			| 1. | Two of the following core courses (6 credits): |  | 
		
			|  | CMSE | 801 | Introduction to Computational Modeling | 3 | 
		
			|  | CMSE | 802 | Methods in Computational Modeling | 3 | 
		
			|  | CMSE | 820 | Mathematical Foundations of Data Science | 3 | 
		
			|  | CMSE | 821 | Numerical Methods for Differential Equations | 3 | 
		
			|  | CMSE | 822 | Parallel Computing |  |  |  | 3 | 
		
			|  | CMSE | 823 | Numerical Linear Algebra I |  |  | 3 | 
		
			| 2. | One or more additional courses selected from the following: |  | 
		
			|  | AST | 911 | Numerical Techniques in Astronomy | 2 | 
		
			|  | CEM | 883 | Computational Quantum Chemistry | 3 | 
		
			|  | CEM | 888 | Computational Chemistry |  |  | 3 | 
		
			|  | CMSE | 801 | Introduction to Computational Modeling | 3 | 
		
			|  | CMSE | 802 | Methods in Computational Modeling | 3 | 
		
			|  | CMSE | 820 | Mathematical Foundations of Data Science | 3 | 
		
			|  | CMSE | 821 | Numerical Methods for Differential Equations | 3 | 
		
			|  | CMSE | 822 | Parallel Computing |  |  |  | 3 | 
		
			|  | CMSE | 823 | Numerical Linear Algebra I |  |  | 3 | 
		
			|  | CSE | 836 | Probabilistic Models and Algorithms in Computational Biology | 3 | 
		
			|  | CSE | 845 | Multi-disciplinary Research Methods for the Study of Evolution | 3 | 
		
			|  | CSE | 881 | Data Mining |  |  |  |  | 3 | 
		
			|  | ECE | 837 | Computational Methods in Electromagnetics | 3 | 
		
			|  | ME | 835 | Turbulence Modeling and Simulation | 3 | 
		
			|  | ME | 840 | Computational Fluid Dynamics and Heat Transfer | 3 | 
		
			|  | ME | 872 | Finite Element Method |  |  | 3 | 
		
			|  | MTH | 451 | Numerical Analysis I |  |  |  | 3 | 
		
			|  | MTH | 452 | Numerical Analysis II |  |  |  | 3 | 
		
			|  | MTH | 850 | Numerical Analysis I |  |  |  | 3 | 
		
			|  | MTH | 851 | Numerical Analysis II |  |  |  | 3 | 
		
			|  | MTH | 852 | Numerical Methods for Ordinary Differential Equations | 3 | 
		
			|  | MTH | 950 | Numerical Methods for Partial Differential Equations I | 3 | 
		
			|  | MTH | 951 | Numerical Methods for Partial Differential Equations II | 3 | 
		
			|  | MTH | 995 | Special Topics in Numerical Analysis and Operations Research | 3 to 6 | 
		
			|  | PHY | 480 | Computational Physics |  |  | 3 | 
		
			|  | PHY | 915 | Computational Condensed Matter Physics | 2 | 
		
			|  | PHY | 919 | Modern Electronic Structure Theory | 2 | 
		
			|  | PHY | 950 | Data Analysis Methods for High-Energy and Nuclear Physics | 2 | 
		
			|  | PHY | 998 | High Performance Computing and Computational Tools for Nuclear Physics | 2 | 
		
			|  | PLB | 810 | Theories and Practices in Bioinformatics | 3 | 
		
			|  | QB | 826 | Introduction to Quantitative Biology Techniques | 1 | 
		
			|  | STT | 461 | Computations in Probability and Statistics | 3 | 
		
			|  | STT | 465 | Bayesian Statistical Methods |  | 3 | 
		
			|  | STT | 802 | Statistical Computation |  |  | 3 | 
		
			|  | STT | 874 | Introduction to Bayesian Analysis | 3 | 
		
			|  | Courses used to fulfill requirement 1. may not be used to fulfill this requirement. Additional courses at the 400-level or above may be used to fulfill this requirement if approved by the CMSE graduate advisor. Students must have a minimum 3.0 grade-point average in courses applied to the certificate in order for it to be awarded. |