К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
Statistical Learning · LearnSpace
Назад в каталог
courseraАнализ данных

Statistical Learning

Курс от Illinois Tech
Средний≈ 114.3 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course offers a deep dive into the world of statistical analysis, equipping learners with cutting-edge techniques to understand and interpret data effectively. We explore a range of methodologies, from regression and classification to advanced approaches like kernel methods and support vector machines, all designed to enhance your data analysis skills. Our journey is guided by the well-known textbook "The Elements of Statistical Learning" by T. Hastie, R. Tibshirani, and J. Friedman. This course provides examples written in Python. Your system should have Python 3.8 or higher, as well as essential libraries such as NumPy, pandas, matplotlib, seaborn, scikit-learn, SciPy, and PyTorch. These tools not only support the learning process but also prepare you for real-world data analysis challenges. Whether you're aiming to refine your expertise or just starting out in the field of data science, this course provides the knowledge and tools to transform your understanding and application of statistical learning. It's a perfect blend of theory and practice, ideal for anyone looking to enhance their skills in data interpretation and analysis.

Навыки, которые вы освоите

Statistical ModelingUnsupervised LearningModel EvaluationRegression AnalysisSupervised LearningBayesian StatisticsMachine Learning AlgorithmsMachine LearningLogistic RegressionStatistical InferenceData AnalysisStatistical MethodsApplied Machine LearningStatistical Machine LearningPredictive ModelingData ScienceStatistical AnalysisStatisticsMachine Learning MethodsStatistical Programming

Программа курса

9 модулей · 170 учебных материалов

01Module 1: Statistical Learning - Terminology and Ideas19 материалов

Course Welcome

Instructor WelcomeВидеоCourse OverviewВидеоSyllabusЧтениеMeet and Greet DiscussionОбсуждение

Module 1 Introduction: What is Statistical Learning?

Учитесь у экспертов

Shahrzad (Sara) Jamshidi

Преподаватель курса

Statistical Learning
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 114.3 ч

9 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
Module 1 IntroductionВидео
What is statistical learning?Видео
What is Statistical Learning ReadingЧтение
What is Statistical Learning QuizЗадание

Lesson 1: Terminology and Types of Data

Terminology and Types of Data ReadingЧтениеTypes of Data ВидеоModels in Statistical LearningВидеоModel Selection ВидеоTerminology and Types of Data QuizЗадание

Lesson 2: Formal Description of Statistical Learning

Formal Description of Statistical Learning ReadingЧтениеFormal Description of Statistical LearningВидеоFormal Description of Statistical Learning QuizЗаданиеCoding ExerciseЛабораторная

Module 1 Summative Assessment

Module 1 Summative AssessmentЗадание

Module 1 Summary

Module 1 SummaryЧтение
02Module 2: Linear Regression Methods27 материалов

Module 2 Introduction

Module 2 IntroductionВидеоModule 2 Introduction ReadingЧтение

Lesson 1: Linear Regression and Least Squares

Linear Regression and Least Squares ReadingЧтениеWhat is Linear Regression? - Part 1ВидеоWhat is Linear Regression? - Part 2ВидеоLinear RegressionВидеоLinear Regression AssumptionsВидеоStatistical ToolsВидеоLinear Regression and Least Squares QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 2: Modification of Linear Regression: Subset Selection

Modification of Linear Regression: Subset Selection ReadingsЧтениеSubset SelectionВидеоModification of Linear Regression: Subset Selection QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 3: Coefficient Shrinkage for Linear Regression: Ridge Regression and LASSO

Coefficient Shrinkage for Linear Regression: Ridge Regression and LASSO ReadingsЧтениеRidge RegressionВидеоLASSOВидеоCoefficient Shrinkage for Linear Regression: Ridge Regression and LASSO QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 4: Data Transformations and Linear Regression

Data Transformations and Linear Regression ReadingЧтениеData Transformation Examples and Linear Regressions ВидеоData Transformations and Linear Regression QuizЗадание

Module 2 Summative Assessment

Module 2 Summative AssessmentЗадание

Module 2 Summary

Module 2 SummaryЧтение
03Module 3: Linear Classification Methods21 материалов

Module 3 Introduction

Module 3 IntroductionВидеоModule 3 Introduction ReadingЧтение

Lesson 1: Linear Regression of an Indicator Matrix

Linear Regression of an Indicator Matrix ReadingsЧтениеClassification with Linear RegressionВидеоLinear Regression and Indicator MatricesВидеоLinear Regression of an Indicator Matrix QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 2: Linear Discriminant Analysis (LDA)

Linear Discriminant Analysis (LDA) ReadingsЧтениеLinear Discriminant Analysis (LDA)ВидеоLinear Discriminant Analysis (LDA) QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 3: Logistic Regression

Logistic Regression ReadingsЧтениеLogistic Regression ВидеоLogistic Regression QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Module 3 Summative Assessment

Module 3 Summative AssessmentЗадание

Module 3 Summary

Module 3 SummaryЧтениеInsights from an Industry Leader: Learn More About Our ProgramЧтение
04Module 4: Basis Expansion Methods20 материалов

Module 4 Introduction

Module 4 IntroductionВидеоModule 4 Introduction ReadingЧтениеWhat are basis expansion methods?Видео

Lesson 1: Piecewise polynomials

Piecewise Polynomials ReadingsЧтениеPiecewise Polynomials, the Method and Theory ВидеоPiecewise polynomials QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 2: Smoothing Splines

Smoothing Splines ReadingsЧтениеSmoothing Splines ВидеоSmoothing Splines QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 3: Regularization via Reproducing Kernel Hilbert Spaces

Regularization via Reproducing Kernel Hilbert Spaces ReadingsЧтениеRegularization and Kernel FunctionsВидеоRegularization via Reproducing Kernel Hilbert Spaces QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Module 4 Summative Assessment

Module 4 Summative AssessmentЗадание

Module 4 Summary

Module 4 SummaryЧтение
05Module 5: Kernel Smoothing Methods 14 материалов

Module 5 Introduction

Module 5 IntroductionВидеоModule 5 Introduction ReadingЧтение

Lesson 1: Kernel Smoothers

Kernel Smoothers ReadingsЧтениеKernel Smoothers and kNNВидеоKernel Smoothers QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 2: Local Regression

Local Regression ReadingsЧтениеLocal Regression ВидеоLocal Regression QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Module 5 Summative Assessment

Module 5 Summative AssessmentЗадание

Module 5 Summary

Module 5 SummaryЧтение
06Module 6: Model Assessment and Selection30 материалов

Module 6 Introduction

Module 6 IntroductionВидеоModule 6 Introduction ReadingsЧтение

Lesson 1: Bias, Variance and Model Complexity

Bias, Variance and Model Complexity ReadingsЧтениеBias, Variance and Model Complexity ВидеоThe Bias-Variance DecompositionВидеоBias, Variance and Model ComplexityЗаданиеCoding ExampleЛабораторная

Lesson 2: Bayesian Approach and BIC

Bayesian Approach and BIC ReadingsЧтениеAIC and BIC ВидеоMinimum Description Length (MDL)ВидеоBayesian Approach and BIC QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 3: Vapnik-Chernovenkis (VC) Dimension

Vapnik-Chervonenkis (VC) Dimension ReadingsЧтениеVapnik-Chervonenkis (VC) Dimension ВидеоVapnik-Chervonenkis (VC) Dimension QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 4: Cross Validation

Cross Validation ReadingsЧтениеK-fold Cross Validation ВидеоCross Validation QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 5: Bootstrapping

Bootstrapping ReadingsЧтениеBootstrappingВидеоBootstrapping QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Module 6 Summative Assessment

Module 6 Summative AssessmentЗадание

Module 6 Summary

Module 6 SummaryЧтение
07Module 7: Maximum Likelihood Inference14 материалов

Module 7 Introduction

Module 7 IntroductionВидеоModule 7 Introduction ReadingЧтение

Lesson 1: Maximum Likelihood Inference

Maximum Likelihood Inference ReadingЧтениеMaximum Likelihood Inference - Part 1ВидеоMaximum Likelihood Inference - Part 2ВидеоMaximum Likelihood Inference Quiz- Part 1ЗаданиеMaximum Likelihood Inference Quiz - Part 2Задание

Lesson 2: Bayesian Inference

Bayesian Inference ReadingsЧтениеBayesian Inference ВидеоBayesian Inference QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Module 7 Summative Assessment

Module 7 Summative AssessmentЗадание

Module 7 Summary

Module 7 SummaryЧтение
08Module 8: Advanced Topics24 материалов

Module 8 Introduction

Module 8 IntroductionВидео

Lesson 1: Additive Models and Trees

Additive Models and Trees ReadingsЧтениеTree Models - Part 1ВидеоTree Models - Part 2ВидеоAdditive Models and Trees QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 2: Support Vector Machines

Support Vector Machines ReadingsЧтениеSupport Vector MachinesВидеоSupport Vector Machines QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 3: k-Means Clustering

k-Means Clustering ReadingsЧтениеK-means Clustering Видеоk-Means Clustering QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Lesson 4: Neural Networks

Neural Networks ReadingsЧтениеNeural Networks ВидеоNeural Networks QuizЗаданиеCoding ExampleЛабораторнаяCoding ExerciseЛабораторная

Module 8 Summative Assessment

Module 8 Summative AssessmentЗадание

Module 8 Summary

Module 8 SummaryЧтение
09Summative Course Assessment1 материалов

Summative Course Assessment

Course Summative AssessmentЗадание