CME 100: Vector Calculus for Engineers (ENGR 154)
Computation and visualization using MATLAB. Differential vector calculus: analytic geometry in space, functions of several variables, partial derivatives, gradient, unconstrained maxima and minima, Lagrange multipliers. Introduction to linear algebra: matrix operations, systems of algebraic equations, methods of solution and applications. Integral vector calculus: multiple integrals in Cartesian, cylindrical, and spherical coordinates, line integrals, scalar potential, surface integrals, Green¿s, divergence, and Stokes¿ theorems. Examples and applications drawn from various engineering fields. Prerequisites: 10 units of AP credit (Calc BC with 4 or 5, or Calc AB with 5), or
Math 41 and 42. Note: Students enrolled in section 10002 and 100A02 are required to attend the discussion section (section 03) on Thursdays 4:305:50pm.
Terms: Aut, Win

Units: 5

UG Reqs: GER:DBMath, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Khayms, V. (PI)
;
Mani, A. (PI)
;
Osgood, B. (PI)
;
Ahluwalia, V. (TA)
...
more instructors for CME 100 »
Instructors:
Khayms, V. (PI)
;
Mani, A. (PI)
;
Osgood, B. (PI)
;
Ahluwalia, V. (TA)
;
Genin, M. (TA)
;
Haaland, C. (TA)
;
Harris, S. (TA)
;
Inamdar, A. (TA)
;
Jiang, R. (TA)
;
Li, Y. (TA)
;
Patki, R. (TA)
;
Ruan, K. (TA)
;
Sheshadri, A. (TA)
;
Siripuram, A. (TA)
;
Zhang, W. (TA)
;
de Lichy, C. (TA)
CME 100A: Vector Calculus for Engineers, ACE
Students attend
CME100/ENGR154 lectures with additional recitation sessions; two to four hours per week, emphasizing engineering mathematical applications and collaboration methods. Enrollment by department permission only. Prerequisite: application at:
http://soe.stanford.edu/current_students/edp/programs/ace.html
Terms: Aut, Win

Units: 6

UG Reqs: GER:DBMath, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Khayms, V. (PI)
;
Mani, A. (PI)
;
Osgood, B. (PI)
;
Ahluwalia, V. (TA)
...
more instructors for CME 100A »
Instructors:
Khayms, V. (PI)
;
Mani, A. (PI)
;
Osgood, B. (PI)
;
Ahluwalia, V. (TA)
;
Genin, M. (TA)
;
Inamdar, A. (TA)
;
Jiang, R. (TA)
;
Li, Y. (TA)
;
Patki, R. (TA)
;
Ruan, K. (TA)
;
Sheshadri, A. (TA)
;
Siripuram, A. (TA)
;
Zhang, W. (TA)
;
de Lichy, C. (TA)
CME 102: Ordinary Differential Equations for Engineers (ENGR 155A)
Analytical and numerical methods for solving ordinary differential equations arising in engineering applications: Solution of initial and boundary value problems, series solutions, Laplace transforms, and nonlinear equations; numerical methods for solving ordinary differential equations, accuracy of numerical methods, linear stability theory, finite differences. Introduction to MATLAB programming as a basic tool kit for computations. Problems from various engineering fields. Prerequisite: 10 units of AP credit (Calc BC with 4 or 5, or Calc AB with 5), or
Math 41 and 42. Recommended:
CME100.
Terms: Aut, Win, Spr, Sum

Units: 5

UG Reqs: GER:DBMath, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Le, H. (PI)
;
Moin, P. (PI)
;
Chen, L. (TA)
;
Dancoisne, B. (TA)
...
more instructors for CME 102 »
Instructors:
Le, H. (PI)
;
Moin, P. (PI)
;
Chen, L. (TA)
;
Dancoisne, B. (TA)
;
DebaillonVesque, O. (TA)
;
Dupont, E. (TA)
;
Gao, P. (TA)
;
Patki, R. (TA)
;
Paudel, S. (TA)
;
Shaikh, S. (TA)
;
Sunder Raj, A. (TA)
;
Suresha, S. (TA)
;
de Lichy, C. (TA)
;
shirian, y. (TA)
CME 102A: Ordinary Differential Equations for Engineers, ACE
Students attend
CME102/ENGR155A lectures with additional recitation sessions; two to four hours per week, emphasizing engineering mathematical applications and collaboration methods. Prerequisite: application at:
http://soe.stanford.edu/current_students/edp/programs/ace.html
Terms: Aut, Win, Spr

Units: 6

UG Reqs: GER:DBMath, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Le, H. (PI)
;
Moin, P. (PI)
;
Chen, L. (TA)
;
Dancoisne, B. (TA)
...
more instructors for CME 102A »
Instructors:
Le, H. (PI)
;
Moin, P. (PI)
;
Chen, L. (TA)
;
Dancoisne, B. (TA)
;
Dupont, E. (TA)
;
Gao, P. (TA)
;
Patki, R. (TA)
;
Paudel, S. (TA)
;
Sunder Raj, A. (TA)
;
Suresha, S. (TA)
;
de Lichy, C. (TA)
CME 106: Introduction to Probability and Statistics for Engineers (ENGR 155C)
Probability: random variables, independence, and conditional probability; discrete and continuous distributions, moments, distributions of several random variables. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, nonparametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields. Prerequisite:
CME 100/ENGR154 or
MATH 51 or 52.
Terms: Win, Sum

Units: 4

UG Reqs: GER:DBMath, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Khayms, V. (PI)
;
Ahluwalia, V. (TA)
;
Hegde, V. (TA)
;
Katanforoosh, K. (TA)
...
more instructors for CME 106 »
Instructors:
Khayms, V. (PI)
;
Ahluwalia, V. (TA)
;
Hegde, V. (TA)
;
Katanforoosh, K. (TA)
;
Kumar, P. (TA)
;
Maher, G. (TA)
;
Martin, E. (TA)
;
Santucci, A. (TA)
CME 108: Introduction to Scientific Computing (MATH 114)
Introduction to Scientific Computing Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floatingpoint arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness. Implementation of numerical methods in MATLAB programming assignments. Prerequisites:
MATH 51, 52, 53; prior programming experience (MATLAB or other language at level of
CS 106A or higher).nGraduate students should take it for 3 units and undergraduate students should take it for 4 units.
Terms: Win, Sum

Units: 34

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Dunham, E. (PI)
;
Allison, K. (TA)
CME 151: Introduction to Data Visualization
Bring your data to life with beautiful and interactive visualizations. This course is designed to provide practical experience on combining data science and graphic design to effectively communicate knowledge buried inside complex data. Each lecture will explore a different set of free industrystandard tools, for example d3.js, three.js, ggplots2, and processing; enabling students to think critically about how to architect their own interactive visualization for data exploration, web, presentations, and publications. Geared towards scientists and engineers, and with a particular emphasis on web, this course assumes an advanced background in programming methodology in multiple languages (particularly R and Javascript). Assignments are short and focus on visual experimentation with interesting data sets or the students' own data. Topics: data, visualization, web. Prerequisites: some experience with general programming is required to understand the lectures and assignments.
Terms: Aut, Win, Spr

Units: 1

Grading: Satisfactory/No Credit
Instructors:
Deriso, D. (PI)
CME 192: Introduction to MATLAB
This short course runs for the first eight weeks of the quarter and is offered each quarter during the academic year. It is highly recommended for students with no prior programming experience who are expected to use MATLAB in math, science, or engineering courses. It will consist of interactive lectures and applicationbased assignments.nThe goal of the short course is to make students fluent in MATLAB and to provide familiarity with its wide array of features. The course covers an introduction of basic programming concepts, data structures, and control/flow; and an introduction to scientific computing in MATLAB, scripts, functions, visualization, simulation, efficient algorithm implementation, toolboxes, and more.
Terms: Aut, Win, Spr

Units: 1

Grading: Satisfactory/No Credit
Instructors:
Yu, J. (PI)
CME 193: Introduction to Scientific Python
This short course runs for the first eight weeks of the quarter and is offered each quarter during the academic year. It is recommended for students who want to use Python in math, science, or engineering courses and for students who want to learn the basics of Python programming. The goal of the short course is to familiarize students with Python¿s tools for scientific computing. Lectures will be interactive with a focus on learning by example, and assignments will be applicationdriven. Some prior programming experience is highly recommended.nTopics covered include control flow, basic data structures, File I/O, and an introduction to NumPy/SciPy.
Terms: Aut, Win, Spr

Units: 1

Grading: Satisfactory/No Credit
Instructors:
de Oliveira, L. (PI)
CME 204: Partial Differential Equations in Engineering (ME 300B)
Geometric interpretation of partial differential equation (PDE) characteristics; solution of first order PDEs and classification of secondorder PDEs; selfsimilarity; separation of variables as applied to parabolic, hyperbolic, and elliptic PDEs; special functions; eigenfunction expansions; the method of characteristics. If time permits, Fourier integrals and transforms, Laplace transforms. Prerequisite:
CME 200/
ME 300A, equivalent, or consent of instructor.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
Instructors:
Lele, S. (PI)
;
Ghate, A. (TA)
;
Inamdar, A. (TA)
;
Wong, M. (TA)
...
more instructors for CME 204 »
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