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@data-140-berkeley

UC Berkeley Data 140

UC Berkeley Probability for Data Science Course
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Data C140

An introduction to probability, emphasizing the combined use of mathematics and programming. Discrete and continuous families of distributions. Bounds and approximations. Transforms and convergence. Markov chains and Markov Chain Monte Carlo. Dependence, conditioning, Bayesian methods. Maximum likelihood, least squares prediction, the multivariate normal, and multiple regression. Random permutations, symmetry, and order statistics. Use of numerical computation, graphics, simulation, and computer algebra.

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  1. data-140-berkeley.github.io data-140-berkeley.github.io Public

    UC Berkeley Data 140 Course Website

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  2. textbook textbook Public

    UC Berkeley Data 140 Textbook

    Jupyter Notebook 33 28

  3. materials-fa25 materials-fa25 Public

    Jupyter Notebook 1 2

  4. prob140 prob140 Public

    A Berkeley library for probability theory.

    Jupyter Notebook 15 2

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