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Supervised Machine Learning · LearnSpace
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Supervised Machine Learning

Курс от Coursera
Средний≈ 16.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Build practical supervised machine learning skills by working through the kinds of tasks you may see in data science, machine learning, and AI-related roles. In this course, you’ll learn how to turn business problems into clear ML tasks, choose the right modeling approach, and build supervised learning models for classification, regression, forecasting, and tabular prediction problems. This is not a traditional lecture-by-lecture course. The experience is organized around workplace skills and job tasks, so you can focus on what you need to perform the work. You’ll start by checking your current skills, then personalize your path by reviewing only the lessons that match your goals and prior knowledge. When you already know a skill, you can move ahead. You’ll learn from curated lessons across expert instructors, with each resource selected for the specific skill it teaches best. By completing this course, you can strengthen your readiness for roles such as data analyst, junior data scientist, machine learning associate, or AI practitioner.

Навыки, которые вы освоите

Machine Learning AlgorithmsApplied Machine LearningPredictive ModelingClassification And Regression Tree (CART)Statistical Machine LearningSupervised LearningMachine Learning MethodsDecision Tree LearningArtificial Intelligence and Machine Learning (AI/ML)Model TrainingRandom Forest AlgorithmFine-tuningLogistic RegressionModel EvaluationRegression AnalysisClassification AlgorithmsModel OptimizationMachine Learning

Программа курса

5 модулей · 60 учебных материалов

01Start Here: Get Oriented and Check Your Skills5 материалов

How This Skill-Based Course Works

Start Here: How This Skill-Based Course WorksЧтениеSkill Diagnostic: Find Your Recommended Starting PointЗадание

Demonstrate Your Skills

Skill Assessment Task 1: Plan and Select Your ML ApproachЗаданиеSkill Assessment Task 2: Build Linear Models and SVMs

Учитесь у экспертов

Professionals from the Industry

Преподаватель курса

Supervised Machine 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

≈ 16.8 ч

5 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
Задание
Skill Assessment Task 3: Build Tree-Based and Ensemble ModelsЗадание
02Job Task 1: Plan and Select Your ML Approach14 материалов

Job Skill: Translate business problems into ML tasks with clear objectives

What Makes a Real-World ML Project Successful?ВидеоWhat Makes a Problem Statement Good or Bad?ЧтениеFixing and Framing ML Problems Across DomainsЧтениеHow to Identify and Structure an ML ProblemЧтениеSuccess Metrics and Real-World ConstraintsЧтениеDefine Your Own ML ProblemЛабораторнаяKnowledge Check: ML Problem FormulationЗадание

Job Skill: Select and justify appropriate algorithms for specific problem requirements based on data and constraints

Choosing the Right Model Isn't Just About AccuracyВидеоWhy Baselines Matter: Measuring Progress with Simple ModelsЧтениеEstablishing a Baseline – Part 1: Training Simple ModelsВидеоEstablishing a Baseline – Part 2: Evaluation and Model SelectionВидеоChoosing the Right Advanced Model for the Right TaskЧтениеTrain and Evaluate Your Baseline ModelsЛабораторная
03Job Task 2: Build Linear Models and SVMs18 материалов

Job Skill: Implement and optimize linear models

Regression in Action: Predicting Sales From Advertising ВидеоWhat Is Linear Regression and How Does It Work? ЧтениеEvaluating a Linear Regression ModelЧтениеUnderstanding Regression Through a Real-World ExampleВидеоScript-Building and Evaluating a Simple Linear Regression ModelВидеоPredicting House Prices Using Linear RegressionЛабораторнаяKnowledge Check: Linear Regression Key ConceptsЗаданиеWhat Is Logistic Regression and Why Do We Use It? ЧтениеGetting Started with Logistic Regression for Binary ClassificationВидеоEvaluating Binary Classification Models with Logistic RegressionВидеоPredicting Loan Approval Using Logistic RegressionЛабораторная

Job Skill: Apply SVMs and kernel methods

How Support Vector Machines Make Decisions ЧтениеUnderstanding the Kernel Trick in SVMsЧтениеUsing SVMs to Recognize Handwritten DigitsВидеоHow SVMs Make Decisions: Margins and Support VectorsВидеоUsing the RBF Kernel to Improve ClassificationВидеоClassifying Handwritten Digits Using SVMsЛабораторная
04Job Task 3: Build Tree-Based and Ensemble Models21 материалов

Job Skill: Build and tune tree-based models

Why Single Decision Trees Can Overfit: A Visual PrimerВидеоUnderstanding Bagging and Random Forests ЧтениеUnderstanding Hyperparameters in Random ForestsЧтениеRandom Forest for Classification: Iris Dataset WalkthroughВидеоRandom Forest for Regression: Predicting House PricesВидео Bagging in Action: Predicting Customer Churn with Random ForestЛабораторнаяKnowledge Check: Bagging and Random ForestsЗаданиеImplementing XGBoost and LightGBM for Boosted ClassificationВидеоHyperparameter Tuning with GridSearchCV: Optimizing XGBoostВидеоTuning Boosting Models: Key Hyperparameters ExplainedЧтениеUsing Boosting Models to Predict Heart DiseaseЛабораторная

Job Skill: Design and build ensemble methods

How Bagging Stabilizes Predictions and Reduces VarianceВидеоHow Boosting Learns from Mistakes — One Model at a TimeВидеоImplementing XGBoost and LightGBM for Boosted ClassificationВидеоBoosting Algorithms Explained: From AdaBoost to XGBoost & LightGBMЧтениеUsing Boosting Models to Predict Heart DiseaseЛабораторнаяWhat Is Stacking? A Simple Visual ExplanationВидео
05Wrap Up: Review Your Skill Achievement and Choose Your Next Path2 материалов

Summarize and Share Your Skills

Turn Your Assessment Work into Career Talking PointsЧтение

Continue Your Skill Journey

Continue Your Skill JourneyЧтение
Train an Advanced Model on Your DatasetЛабораторная
Knowledge Check: SVM Key ConceptsЗадание
How to Train a Stacking Model (Without Leaking Data)Видео
When and How to Use Stacking EffectivelyЧтение
Stacking in Practice: Understanding the StackingClassifier StructureЧтение
Building and Evaluating a StackingClassifier on Loan Default DataЛабораторная