# Alternative Elective Courses

The following electives can be considered as technical electives for ES students:

**All non-ES electives can only be counted towards BSEE degree if no ES elective is offered. All non-ES electives must be approved by the department chair prior to registration.**

Course | Title | Description | Notes |
---|---|---|---|

MATH 431 | Applied Partial Differential Equations (4) | A course in partial differential equations (PDEs). Topics include: mathematical models in physics, theory, and solution of quasi-linear first-order PDEs; second-order linear and nonlinear PDEs, including applications. Fourier series, boundary-value problems, Fourier and Laplace transforms. Numerical methods and solutions. Prerequisite: MATH 241 or consent of instructor. | If you take this course you can become MATH Minor and it can be used as your Technical Elective. |

MATH 352 | Numerical Analysis (4) | Selected numerical and iterative processes for solving mathematical problems and their applications. Topics include finding roots with bisection and Newton’s method; solving systems of linear equations using LU decomposition and Gauss-Seidel methods; polynomial approximation using Taylor’s Theorem, Lagrange interpolations, and the theory of spline functions; numerical integration using Simpson’s rule and Gaussian integration; Prerequisite: Math 241, some programming skills | |

MATH 470 | Mathematical and Statistical Modeling (4) | The process of expressing scientific principles, experiments, and conjectures in mathematical terms. Topics include: gathering reliable data, exposing underlying assumptions, variables, relationships, levels, refining of models, and stochastic models. Deterministic vs. stochastic, discrete vs continuous, and deductive vs statistical models. Prerequisite: Math 211 | Please see MATH Catalog |

MATH 445 | Mathematical Statistics and Operations Research (4) | Topics include: properties of statistics, convergence in probability, theory of estimation and confidence intervals, Bayesian statistics, tests of significance, power and uniformly most powerful tests, random processes (with emphasis on queuing theory), and stationarity. Prerequisite: Math 345 | ES 345 counts as prerequisite |

MATH 465 | Experimental Design and Regression Analysis (4) | Advanced course in simple and multiple linear regression analysis; nonlinear and nonparametric regression analysis. Design of experiments and analysis of variance including one-way, two-way and block design; nonparametric techniques and multiple comparison methods. Prerequisite: MATH 265 and either MATH 241 or another course in linear algebra, and MATH 345 or consent of instructor. | |

MATH 316 | Graph Theory & Combinatorics (3) | Spring course only (generally) - Set theory, counting techniques such as permutations, combinations, generating functions, partitions and recurrence relations, Polya’s theorem, Hamiltonian and Eulerian properties of graphs, matchings, trees, coloring problems, and planarity. Applications in many disciplines. Prerequisite: MATH 142 or MATH 200 or MATH 220 or consent of instructor. | In general Graph Theory can be very useful for the Networking class (ES 465) - NOTE Students may not earn credit for both MATH 316 and MATH 416. |

MATH 345 | Probability Theory (4) | Topics include probability spaces, discrete and continuous random variables, selected probability distributions for random phenomena, distributions of functions of random variables, moment generating functions, expected value, covariance and correlation, conditional expectation, law of large numbers and central limit theorem, and sampling distribution of estimators | Allowed only if the student is graduating and cannot take equivalent ES 345 |

MATH 165 (substitute for MATH 142 only) | Elementary Applied Statistics (4) | This course is a technology-intensive introduction to elementary statistics. Topics include: elementary descriptive and inferential statistics and their application to the behavioral, natural, and social sciences; sampling; special distributions; central limit theorem; estimation; tests of hypothesis; analysis of variance; linear regression; and correlation. Satisfies the GE Area B4 requirement for mathematics. | You can take this course in place of MATH 142. DO NOT take MATH 131, as MATH 131 may not be very useful! |

MATH 220 (substitute for MATH 142 only) | Reasoning and Proof (4) | This course will teach students to analyze and evaluate scientific and rhetorical reasoning, with emphasis on the reasoning used in Mathematical proofs. Students will identify and evaluate unstated assumptions in statistical tables and charts from real-world media, submit coherent and original proofs of theorems, and develop verbal and non-verbal skills for making persuasive oral arguments and presentations on mathematical topics. | You can take this course in place of MATH 142.MATH 220 is somewhat similar to MATH 142. DO NOT take MATH 131, as MATH 131 may not be very useful! |

Course | Title | Description | Notes |
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PHYS 314 | Introduction to Physics III (Modern Physics) (3) | The continuation of PHYS 214. Special relativity, elementary quantum mechanics, the Bohr atom and deBroglie waves, the Schrödinger wave equation with applications to simple one-dimensional problems and to atomic structure, elementary nuclear physics, introduction to equilibrium statistical mechanics, the partition function, Boltzmann statistics. Prerequisites: PHYS 214 and MATH 261 | All senior EE students meet the prerequisites This course is a good foundation for physics of semiconducting devices phys 475, which is cross listed as ES 432. This course is the prerequisite for several other recommended physics courses for EE students. |

PHYS 340 | Light and Optics (3) | The quantum theory of light, coherence, interference, diffraction and polarization, masers, lasers, geometrical optics, spectroscopy. Prerequisite: PHYS 314 or 325. | Talk to the instructor to remove PHYS 314 requirement. A very good course for EE students who are interested in optics and lasers |

PHYS 325 | Introduction To Mathematical Physics (3) | This course examines advanced mathematical methods and serves as a foundation for future courses. Topics include coordinate systems and vectors, vector calculus, series expansions, differential equations, orthonomal functions, solutions of systems of linear equations, matrices and tensors, complex numbers, eigenvalues and eigenfunctions, Fourier series and Fourier integrals, and use of mathematical symbolic processing software. Prerequisites: PHYS 214 and MATH 261, or consent of instructor. | All senior EE students meet the prerequisites. This is a very good course summing up all your applied math skills! |

PHYS 366 | Intermediate Experimental Physics (3) | Lecture 2 hours; laboratory 3 hours. An introduction to contemporary techniques and problems in physics. Selected topics in lasers and photonics, materials science (including high-magnetic field measurements and surface analysis using scanning electron and atomic force microscopy), X-ray analysis, applied nuclear physics, and adaptive optics. Prerequisites: PHYS 314 and 216, or consent of instructor. | EE students may need to take PHYS 314. Talk to the instructor. A highly useful course for EE students interested in introductory materials analysis and the use of high level instruments in the Keck microanalysis laboratory. |

PHYS 466 | Advanced Experimental Physics (3) | Lecture, 2 hours; laboratory, 3 hours. Advanced topics in lasers and photonics, materials science (including high-magnetic field measurements and surface analysis using scanning electron and atomic force microscopy), X-ray analysis, applied nuclear physics, and adaptive optics. Prerequisites: PHYS 314 and 216, or consent of instructor | EE students may need to take PHYS 314. Talk to the instructor. Recommended for students interested in advanced materials analysis. |

PHYS 475 | Physics of Semiconductor Devices (3) | A detailed study of semiconductors and their applications. Topics include semiconductor materials, crystal structure and growth, energy bands and charge carriers, conductivity and mobility, metal-semiconductor and p-n junctions, p-n junction diodes, bipolar junction transistors, field-effect transistors, CCDs, photonic devices, and integrated circuits. Conductivity and contact resistance measurements, I-V and C-V characteristics of diodes, characterization of transistors. Prerequisite: PHYS 314 or consent of instructor. | Talk to the instructor to remove PHYS 314 requirement. Cross-listed as CES 432 and ES 432. |

Course | Title | Description | Notes |
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CS 485 | Artificial Intelligence (3) | This course is a survey of techniques that simulate human intelligence. Topics may include: pattern recognition, general problem solving, adversarial gametree search, decision-making, expert systems, neural networks, fuzzy logic, and genetic algorithms. Prerequisite: CS 315 or consent of instructor. | Talk to the instructor to remove CS 315 requirement.This is cross listed with ES 480 - ES 314 is required for this course. |