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Data Analytics Foundations for Accountancy II · LearnSpace
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Data Analytics Foundations for Accountancy II

Курс от University of Illinois Urbana-Champaign
Начальный≈ 70 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course is closing for new learner enrollment on 9/10/26 and all graded assignments, including peer reviews, must be completed by 8/9/27 to earn a Course Certificate. Welcome to Data Analytics Foundations for Accountancy II! I'm excited to have you in the class and look forward to your contributions to the learning community. To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover each week, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!

Навыки, которые вы освоите

Scikit Learn (Machine Learning Library)Machine LearningRegression AnalysisClassification AlgorithmsMachine Learning AlgorithmsUnsupervised LearningApplied Machine LearningAnomaly DetectionFeature EngineeringMachine Learning MethodsSupervised LearningDecision Tree LearningModel OptimizationModel EvaluationResponsible AIModel TrainingStatistical Machine LearningMachine Learning SoftwareData Ethics

Программа курса

9 модулей · 125 учебных материалов

01Course Orientation10 материалов

About the Course

Welcome to Data Analytics Foundations for Accountancy IIВидеоMeet Professor BrunnerВидеоSyllabusЧтениеAbout the Discussion ForumsЧтение

Учитесь у экспертов

Robert J. Brunner

Professor of Accountancy, Chief Disruption Officer, and Arthur Andersen Faculty Fellow

Data Analytics Foundations for Accountancy II
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

≈ 70 ч

9 модулей

Язык: Английский

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

Часть программы вашего университета
Orientation QuizЗадание
Online Education at Gies College of BusinessЧтение
Learn on Your TermsВидео

About Your Classmates

Updating Your ProfileЧтениеGetting to Know Your ClassmatesОбсуждениеSocial MediaЧтение
02Module 1: Introduction to Machine Learning13 материалов

Module 1 Information

Module 1 OverviewЧтениеIntroduction to Module 1Видео

Lesson 1-1: Artificial Intelligence and Accountancy

Lesson 1-1 ReadingsЧтение

Lesson 1-2: Introduction to Machine Learning

Lesson 1-2 ReadingsЧтениеIntroduction to Machine LearningВидеоIntroduction to Machine Learning NotebookЛабораторная

Lesson 1-3: Introduction to Linear Regression

Introduction to Linear RegressionВидеоIntroduction to Linear Regression NotebookЛабораторная

Lesson 1-4: Introduction to k-Nearest Neighbors

Introduction to k-nnВидеоIntroduction to k-nn NotebookЛабораторная

Module 1 Graded Activities

Module 1 Graded QuizЗаданиеModule 1 Programming AssignmentПрограммированиеModule 1 Programming Assignment NotebookЛабораторная
03Module 2: Fundamental Algorithms15 материалов

Module 2 Information

Module 2 OverviewЧтениеIntroduction to Module 2Видео

Lesson 2-1: Digital Supply Chains

Lesson 2-1 ReadingsЧтениеIntroduction to Fundamental AlgorithmsВидео

Lesson 2-2: Introduction to Logistic Regression

Introduction to Logistics RegressionВидеоIntroduction to Logistic Regression NotebookЛабораторная

Lesson 2-3: Introduction to Decision Trees

Lesson 2-3 ReadingsЧтениеIntroduction to Decision TreesВидеоIntroduction to Decision Trees NotebookЛабораторная

Lesson 2-4: Introduction to Support Vector Machine

Lesson 2-4 ReadingsЧтениеIntroduction to Support Vector MachineВидеоIntroduction to Support Vector Machine NotebookЛабораторная

Module 2 Graded Activities

Module 2 Graded QuizЗаданиеModule 2 Programming AssignmentПрограммированиеModule 2 Programming Assignment NotebookЛабораторная
04Module 3: Practical Concepts in Machine Learning14 материалов

Module 3 Information

Module 3 OverviewЧтениеIntroduction to Module 3Видео

Lesson 3-1: Production Data Analytics

Lesson 3-1 ReadingsЧтениеIntroduction to Modeling SuccessВидео

Lesson 3-2: Introduction to Bagging

Lesson 3-2 ReadingsЧтениеIntroduction to BaggingВидеоIntroduction to Bagging NotebookЛабораторная

Lesson 3-3: Introduction to Boosting

Introduction to BoostingВидеоIntroduction to Boosting NotebookЛабораторная

Lesson 3-4: Introduction to Pipelines

Introduction to ML PipelinesВидеоPractical Concerns in Machine LearningЛабораторная

Module 3 Graded Activities

Module 3 Graded QuizЗаданиеModule 3 Programming AssignmentПрограммированиеModule 3 Programming Assignment NotebookЛабораторная
05Module 4: Overfitting & Regularization15 материалов

Module 4 Information

Module 4 OverviewЧтениеIntroduction to Module 4Видео

Lesson 4-1: Introduction to Overfitting

Lesson 4-1 ReadingsЧтениеIntroduction to OverfittingВидео

Lesson 4-2: Introduction to Cross-Validation

Lesson 4-2 ReadingsЧтениеIntroduction to Cross-ValidationВидеоIntroduction to Cross-Validation NotebookЛабораторная

Lesson 4-3: Introduction to Model-Selection

Lesson 4-3 ReadingsЧтениеIntroduction to Model-SelectionВидеоIntroduction to Model-Selection NotebookЛабораторная

Lesson 4-4: Introduction to Regularization

Introduction to RegularizationВидеоIntroduction to Regularization NotebookЛабораторная

Module 4 Graded Activities

Module 4 Graded QuizЗаданиеModule 4 Programming AssignmentПрограммированиеModule 4 Programming Assignment NotebookЛабораторная
06Module 5: Fundamental Probabilistic Algorithms13 материалов

Module 5 Information

Module 5 OverviewЧтениеIntroduction to Module 5Видео

Lesson 5-1: Machine Learning Workflows

Lesson 5-1 ReadingsЧтениеIntroduction to Practical Machine LearningВидео

Lesson 5-2: Introduction to Naive Bayes

Lesson 5-2 ReadingsЧтениеIntroduction to Naive BayesВидеоIntroduction to Naive Bayes NotebookЛабораторная

Lesson 5-3: Introduction to Gaussian Processes

Lesson 5-3 ReadingsЧтениеIntroduction to Gaussian ProcessesВидеоIntroduction to Gaussian Processes NotebookЛабораторная

Module 5 Graded Activities

Module 5 Graded QuizЗаданиеModule 5 Programming AssignmentПрограммированиеModule 5 Programming Assignment NotebookЛабораторная
07Module 6: Feature Engineering15 материалов

Module 6 Information

Module 6 OverviewЧтениеIntroduction to Module 6Видео

Lesson 6-1: Practical Concerns with Machine Learning

Lesson 6-1 ReadingsЧтениеPractical Concerns with Machine LearningВидео

Lesson 6-2: Introduction to Feature Selection

Introduction to Feature SelectionВидеоIntroduction to Feature Selection NotebookЛабораторная

Lesson 6-3: Introduction to Dimensional Reduction

Lesson 6-3 ReadingsЧтениеIntroduction to Dimension ReductionВидеоIntroduction to Dimension Reduction NotebookЛабораторная

Lesson 6-4: Introduction to Manifold Learning

Lesson 6-4 ReadingsЧтениеIntroduction to Manifold LearningВидеоIntroduction to Manifold Learning NotebookЛабораторная

Module 6 Graded Activities

Module 6 Graded QuizЗаданиеModule 6 Programming AssignmentПрограммированиеModule 6 Programming Assignment NotebookЛабораторная
08Module 7: Introduction to Clustering16 материалов

Module 7 Information

Module 7 OverviewЧтениеIntroduction to Module 7Видео

Lesson 7-1: Introduction to Clustering

Lesson 7-1 ReadingsЧтениеIntroduction to ClusteringВидео

Lesson 7-2: Introduction to Spatial Clustering

Lesson 7-2 ReadingsЧтениеIntroduction to Spatial ClusteringВидеоIntroduction to Spatial Clustering NotebookЛабораторная

Lesson 7-3: Introduction to Density-Based Clustering

Lesson 7-3 ReadingsЧтениеIntroduction to Density-Based ClusteringВидеоIntroduction to Density-Based Clustering NotebookЛабораторная

Lesson 7-4: Introduction to Mixture Models

Lesson 7-4 ReadingsЧтениеIntroduction to Mixture ModelsВидеоIntroduction to Mixture Models NotebookЛабораторная

Module 7 Graded Activities

Module 7 Graded QuizЗаданиеModule 7 Programming AssignmentПрограммированиеModule 7 Programming Assignment NotebookЛабораторная
09Module 8: Introduction to Anomaly Detection14 материалов

Module 8 Information

Module 8 OverviewЧтениеIntroduction to Module 8Видео

Lesson 8-1: Introduction to Anomaly Detection

Lesson 8-1 ReadingsЧтениеIntroduction to Anomaly DetectionВидео

Lesson 8-2: Statistical Anomaly Detection

Statistical Anomaly DetectionВидеоStatistical Anomaly Detection NotebookЛабораторная

Lesson 8-3: Machine Learning and Anomaly Detection

Machine Learning and Anomaly DetectionВидеоMachine Learning and Anomaly Detection NotebookЛабораторная

Module 8 Graded Activities

Module 8 Graded QuizЗаданиеModule 8 Programming AssignmentПрограммированиеModule 8 Programming Assignment NotebookЛабораторнаяCongratulations on completing the course!ЧтениеGet Your Course CertificateЧтениеHow was the coursePLUGIN