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Introduction to Bayesian Statistics for Data Science · LearnSpace
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Introduction to Bayesian Statistics for Data Science

Курс от University of Colorado Boulder
Средний≈ 37.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data science problems. Topics include the use and interpretations of probability theory in Bayesian inference; Bayes’ theorem for statistical parameters; conjugate, improper, and objective priors distributions; data science applications of Bayesian inference; and ethical implications of Bayesian statistics. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Навыки, которые вы освоите

Bayesian StatisticsRegression AnalysisStatistical ModelingProbabilityStatistical InferenceData SciencePredictive AnalyticsStatistical MethodsData EthicsProbability DistributionPredictive Modeling

Программа курса

5 модулей · 69 учебных материалов

01Philosophical Underpinnings of Bayesian Statistics20 материалов

Getting Started

Course Updates and Accessibility SupportЧтениеEarn Academic Credit for your Work!ЧтениеCourse SupportЧтениеAssessment ExpectationsЧтение

Course Introduction

Учитесь у экспертов

Brian Zaharatos

Director, Professional Master’s Degree in Applied Mathematics

Introduction to Bayesian Statistics for Data Science
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Обучение на Coursera

≈ 37.5 ч

5 модулей

Язык: Английский

Субтитры: Венгерский

Часть программы вашего университета
Course IntroductionВидео
Introduce YourselfОбсуждение

Optional Review: Jupyter and R and Tidyvrse

Introduction to Jupyter and RПрограммированиеIntroduction to TidyverseПрограммирование

Comparing Bayesian Statistics to Frequentist Statistics: Stopping Rules

Module 1 Slide DeckЧтениеStopping Rules: Part 1ВидеоDo Stopping Rules Matter? Part 1: ExerciseЛабораторнаяStopping Rules: Part 2Видео

Comparing Bayesian Statistics to Frequentist Statistics: Theory

Comparing Bayesian Statistics to Frequentist Statistics: Part 1ВидеоComparing Bayesian Statistics to Frequentist Statistics: Part 2Видео

Bayes Theorem and Prior Distributions

Derivation of Posterior DistributionВидеоPrior DistributionsВидеоDo Stopping Rules Matter? Part 2: ExerciseЛабораторнаяStopping Rules: Part 3Видео

Module 1 Assignments

Module 1: Philosophical Underpinnings of Bayesian Statistics QuizЗаданиеModule 1 Programming AssignmentПрограммирование
02Introduction to Bayesian Inference and Prediction10 материалов

Comparing Bayesian Inference to Maximum Likelihood Estimate

Maximum Likelihood vs Bayesian InferenceЛабораторнаяComparing Bayesian Inference to Maximum Likelihood: Part 1ВидеоComparing Bayesian Inference to Maximum Likelihood: Part 2Видео

Summarizing the Posterior Distribution

Summarizing the Posterior DistributionВидео

Posterior Predictive

Situating the Posterior PredictiveВидеоDeriving the Posterior Predictive DistributionВидеоPosterior Predictive DistributionЛабораторнаяSimulating the Posterior Predictive DistributionВидео

Module 2 Assignments

Module 2: Introduction to Bayesian Inference and Prediction QuizЗаданиеModule 2 Programming AssignmentПрограммирование
03Introduction to Conjugate Families12 материалов

The Beta-Binomial and Normal-Normal Conjugate Families

Module 3 Slide DeckЧтениеThe Beta-Binomial Conjugate FamilyВидеоPosterior Distributions as a Weighted AverageВидеоNormal-Normal Conjugate FamilyВидео

Conjugate Family Example in R

Probability of a Genetic MarkerЛабораторнаяBeta-binomial Conjugate Family Example in RВидео

Inverse Gamma-Normal Conjugate Family

The Inverse Gamma Distribution: A Prior for Estimating VarianceВидеоThe Inverse Gamma Normal Conjugate Family: Finding the Posterior for the VarianceВидеоNormal-inverse GammaЛабораторнаяThe Inverse Gamma Normal Conjugate Family Example in RВидео

Module 3 Assignments

Module 3: Introduction to Conjugate Families QuizЗаданиеModule 3 Programming AssignmentПрограммирование
04Improper and Objective Priors12 материалов

Improper Priors

Module 4 Slide DeckЧтениеIntroduction to Improper PriorsВидеоImproper PriorsЛабораторнаяExample of Improper Prior in RВидео

Jeffreys' Prior Part 1

Motivating the Objective PriorВидеоJeffreys' PriorВидео

Jeffreys' Prior Part 2

Proof: Jeffreys' Prior is Invariant to ReparameterizationВидеоExample of Deriving Jeffreys' PriorВидеоJeffreys' PriorЛабораторнаяExample of Jeffreys' Prior in RВидео

Module 4 Assignments

Module 4: Improper and Objective Priors QuizЗаданиеModule 4 Programming AssignmentПрограммирование
05Multiparameter Inference15 материалов

Introduction to Multiparameter Bayesian Inference

Module 5 Slide DeckЧтениеMultiparameter Inference: Nuisance ParametersВидеоMultiparameter Inference: Theoretical Example with Improper PriorsВидео

Multiparameter Bayesian Inference: Examples

Inverse and Scaled Inverse Chi Squared DistributionsВидеоEstimating the Mean and Variance of Normally Distributed DataВидео

Multiparameter Bayesian Inference: Applications

Multiparameter Models: Part 1ЛабораторнаяEstimating the Mean and Variance of Normally Distributed Data with Uninformative Priors in RВидеоMultiparameter Models: Part 2ЛабораторнаяEstimating the Mean and Variance of Normally Distributed Data with General Priors in RВидео

Bayesian Linear Regression

Multiparameter Inference: Bayesian Linear Regression ВидеоComparison of Bayesian Linear Regression Parameters to Frequentist Least Squares EstimatorВидеоBayesian Regression ModelingЛабораторнаяBayesian Linear Regression in RВидео

Module 5 Assignments

Module 5: Multiparameter Inference QuizЗаданиеModule 5 Programming AssignmentПрограммирование