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2023 Courses

Explore these Summer 2023 courses and when you're ready, apply to be a visiting Stanford student. Apply early for the best course choice when enrollment opens.

Course List

  • Vector Calculus for Engineers

    Available
    Catalog Number
    CME 100
    Course Cost
    $6410.00
    Population
    High School, Undergraduate, Graduate
    Summary

    Computation and visualization using MATLAB. Differential vector calculus: vector-valued functions, analytic geometry in space, functions of several variables, partial derivatives, gradient, linearization, unconstrained maxima and minima, Lagrange multipliers and applications to trajectory simulation, least squares, and numerical optimization. Introduction to linear algebra: matrix operations, systems of algebraic equations with applications to coordinate transformations and equilibrium problems. Integral vector calculus: multiple integrals in Cartesian, cylindrical, and spherical coordinates, line integrals, scalar potential, surface integrals, Green's, divergence, and Stokes' theorems. Numerous examples and applications drawn from classical mechanics, fluid dynamics and electromagnetism. Placement Diagnostic (recommendation non-binding).

    Download syllabus (pdf)

    Details

    Class Number
    23490
    Units
    5
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Hung Le
    Dates
    -
    Prerequisites

    Knowledge of single-variable calculus equivalent to the content of MATH 19, MATH 20, MATH 21 (e.g., 5 on Calc BC, 4 on Calc BC with MATH 21, 5 on Calc AB with MATH 21)

    Schedule
    T/W/Th, 8:30A-10:20A
    Cross Listings
    ENGR 154
  • Ordinary Differential Equations for Engineers

    Available
    Catalog Number
    CME 102
    Course Cost
    $6410.00
    Population
    High School, Undergraduate, Graduate
    Summary

    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 5, or Calc AB with 5 or placing out of the single variable math placement test: Placement diagnostic), or MATH 19, MATH 20, MATH 21. Recommended: CME100.

    Download syllabus (pdf)

    Details

    Class Number
    6993
    Units
    5
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Hung Le
    Dates
    -
    Prerequisites

    10 units of AP credit (Calc BC with 5, or Calc AB with 5 or placing out of the single variable math placement test , or MATH 19, MATH 20 or MATH 21. Recommended: CME100.

    Schedule
    T/W/Th, 11:30A-1:20P
    Cross Listings
    ENGR 155A
  • Introduction to Probability and Statistics for Engineers

    Available
    Catalog Number
    CME 106
    Course Cost
    $5128.00
    Population
    High School, Undergraduate, Graduate
    Summary

    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, non-parametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields.

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    Details

    Class Number
    4612
    Units
    4
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Vadim Khayms
    Dates
    -
    Prerequisites

    CME 100, ENGR 154, MATH 51 or Math 52

    Schedule
    T/Th, 5:30P-8:00P
    Cross Listings
    ENGR 155C
  • Introduction to Probability and Statistics for Epidemiology

    Available
    Catalog Number
    EPI 259
    Course Cost
    $3846.00
    Population
    Undergraduate, Graduate
    Summary

    Topics: random variables, expectation, variance, probability distributions, the central limit theorem, sampling theory, hypothesis testing, confidence intervals. Correlation, regression, analysis of variance, and nonparametric tests. Introduction to least squares and maximum likelihood estimation. Emphasis is on medical applications. EPI 259 in summer is offered for remote students.

    Details

    Class Number
    22041
    Units
    3
    Interest Area
    Math and Data Science
    Course Format & Length
    Online, 8 weeks
    Instructors
    Kristin Sainani
    Dates
    -
    Schedule
    M/W, 9:30A-11:20A
    Cross Listings
    HUMBIO 89X
  • Linear Algebra, Multivariable Calculus, and Modern Applications

    Available
    Catalog Number
    MATH 51-02
    Course Cost
    $6410.00
    Population
    High School, Undergraduate, Graduate
    Summary

    This course provides unified coverage of linear algebra and multivariable differential calculus. It discusses applications connecting the material to many quantitative fields.  Linear algebra in large dimensions underlies the scientific, data-driven, and computational tasks of the 21st century. The linear algebra portion of the course includes orthogonality, linear independence, matrix algebra, and eigenvalues as well as ubiquitious applications: least squares, linear regression, Markov chains (relevant to population dynamics, molecular chemistry, and PageRank), singular value decomposition (essential in image compression, topic modeling, and data-intensive work in the natural sciences), and more. The multivariable calculus material includes unconstrained optimization via gradients and Hessians (used for energy minimization in physics and chemistry), constrained optimization (via Lagrange multipliers, crucial in economics), gradient descent and the multivariable Chain Rule (which underlie many machine learning algorithms, such as backpropagation), and Newton's method (a crucial part of how GPS works).  The course emphasizes computations alongside an intuitive understanding of key ideas,  making students well-prepared for further study of mathematics and its applications to other fields.  The widespread use of computers makes it more important, not less, for users of math to understand concepts: in all scientific fields, novel users of quantitative tools in the future will be those who understand ideas and how they fit with applications and examples.  This is the only course at Stanford whose syllabus includes nearly all the math background for CS 229, which is why CS 229 and CS 230 specifically recommend it (or other courses resting on it). For frequently asked questions about the differences between Math 51 and CME 100, see the FAQ on the placement page on the math department website.

    Details

    Class Number
    23549
    Units
    5
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Stavrianidi, A.
    Dates
    -
    Prerequisites

    MATH 21, MATH 42, or the math placement diagnostic (offered through the Math Department website) in order to register for this course

    Schedule
    MTWThF, 1:30P-2:50P
  • Theory of Probability

    Available
    Catalog Number
    STATS 116
    Course Cost
    $6410.00
    Population
    High School, Undergraduate, Graduate
    Summary

    Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and densities. Random variables, expectation, independence, conditional probability. Introduction to the laws of large numbers and central limit theorem. 5 units for Undergraduates with required discussion section. 4 units for Graduates, discussion section optional. The section 01 lecture is for UGs only. UGs are required to enroll in one of the sections.

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    Details

    Class Number
    7096
    Units
    5
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Li, H.
    Dates
    -
    Prerequisites

    MATH 52 and familiarity with infinite series, or equivalent.

    Schedule
    MTWTh, 10:30A-11:20A
  • Data Mining and Analysis

    Available
    Catalog Number
    STATS 202
    Course Cost
    $3846.00
    Population
    High School, Undergraduate, Graduate
    Summary

    Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case based methods, and data visualization.

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    Details

    Class Number
    8606
    Units
    3
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Tran, Linh
    Dates
    -
    Prerequisites

    Introductory courses in statistics or probability (e.g., STATS 60), linear algebra (e.g., MATH 51), and computer programming (e.g., CS 105).

    Schedule
    M/W, 4:30P-5:50P
  • Introduction to Regression Models and Analysis of Variance

    Available
    Catalog Number
    STATS 203V
    Course Cost
    $3846.00
    Population
    Undergraduate, Graduate
    Summary

    Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design.

    Details

    Class Number
    11831
    Units
    3
    Interest Area
    Math and Data Science
    Course Format & Length
    Online, 8 weeks
    Instructors
    Dey, A.
    Dates
    -
    Prerequisites

    Pre- or corequisite: STATS 200.

    Schedule
    online asynchronous
  • Introduction to Statistical Learning

    Available
    Catalog Number
    STATS 216V
    Course Cost
    $3846.00
    Population
    Undergraduate, Graduate
    Summary

    Overview of supervised learning, with a focus on regression and classification methods. Syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines; Some unsupervised learning: principal components and clustering (k-means and hierarchical). Computing is done in R, through tutorial sessions and homework assignments. This math-light course is offered remotely only via video segments (MOOC style). TAs will host remote weekly office hours using an online platform such as Google Hangout or BlueJeans. There are four homework assignments, a midterm, and a final exam, all of which are administered remotely.

    Download syllabus (pdf)

    Details

    Class Number
    11740
    Units
    3
    Interest Area
    Math and Data Science
    Course Format & Length
    Online, 8 weeks
    Instructors
    Sood, A.
    Dates
    -
    Prerequisites

    Introductory courses in statistics or probability (e.g., STATS 60), linear algebra (e.g., MATH 51), and computer programming (e.g., CS 105).

    Schedule
    T/Th, 10:30A-11:50A
  • Introduction to Stochastic Processes I

    Available
    Catalog Number
    STATS 217
    Course Cost
    $3846.00
    Population
    Undergraduate, Graduate
    Summary

    Discrete and continuous time Markov chains, poisson processes, random walks, branching processes, first passage times, recurrence and transience, stationary distributions. Non-Statistics masters students may want to consider taking STATS 215 instead.

    Download syllabus (pdf)

    Details

    Class Number
    23427
    Units
    3
    Interest Area
    Math and Data Science
    Course Format & Length
    In-Person, 8 weeks
    Instructors
    Hartog, W.
    Dates
    -
    Prerequisites

    STATS 116 or consent of instructor

    Schedule
    T/Th, 10:30A-11:50A

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Students who take Summer Session courses are awarded Stanford credit. Course costs are set by the university, based on number of units.
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