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AutoML: Build ML Models without Code · LearnSpace
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AutoML: Build ML Models without Code

Курс от Edureka
Средний≈ 9.4 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Cloud-powered machine learning is now within reach for every data professional. This course teaches you to train, deploy, and monitor production-ready ML models using Google Vertex AI's AutoML platform — covering structured data, images, and text — entirely through the web console with no coding required. Throughout this course, you'll move through the complete AutoML lifecycle: platform setup, dataset management, advanced model training across vision and NLP domains, real-world deployment, and business tool integration — all backed by step-by-step video demonstrations on Google Cloud. You're expected to set up your own Google Cloud account, follow along with each instructor demonstration in the console, and pause the video as needed to complete each configuration or training step at your own pace. By the end of this course, you'll be able to: - Configure Google Cloud Platform and Vertex AI to set up and manage AutoML workflows for structured, image, and text datasets. - Train classification and regression models using AutoML Tables and interpret automated feature engineering and model evaluation results. - Build and evaluate AutoML Vision and Natural Language models for image classification, object detection, and text sentiment analysis. - Deploy trained models for online predictions, integrate outputs with Google Sheets and BigQuery, and monitor model performance through the cloud console. This course is designed for a diverse audience: data analysts, business intelligence professionals, product managers, domain experts, and non-technical professionals looking to leverage cloud ML capabilities to automate predictions and integrate AI into business workflows. Basic familiarity with data and machine learning concept, is recommended before enrolling. Step into cloud-powered ML and master the skills to build, deploy, and manage intelligent AutoML models that deliver measurable business impact — without writing a single line of code.

Навыки, которые вы освоите

Model DeploymentReinforcement LearningConvolutional Neural NetworksFeature EngineeringNatural Language ProcessingImage AnalysisModel EvaluationModel TrainingGoogle Cloud PlatformComputer VisionData SciencePredictive ModelingCloud PlatformsMachine LearningApplied Machine LearningDeep LearningMachine Learning SoftwareCloud DeploymentNo-Code DevelopmentGoogle Sheets

Программа курса

4 модулей · 71 учебных материалов

01AutoML Platform Setup & Hands-On Experience30 материалов

Cloud ML & AutoML Platform Setup

Course IntroductionВидеоCourse Outline: Complete No-Code Advanced ML & Deployment Journey ЧтениеCloud Machine Learning Platform OverviewВидеоBenefits and Business Value of Cloud Machine LearningВидео

Учитесь у экспертов

Edureka

Преподаватель курса

AutoML: Build ML Models without Code
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 9.4 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский

Часть программы вашего университета
Platform Architecture and WorkflowВидео
AutoML Capabilities and FeaturesВидео
Hands-On: Configuring Google Cloud Platform for Machine LearningВидео
Hands-On: Setting Up Vertex AI Environment for AutoML WorkflowsВидео
Hands-On: Uploading and Managing Datasets in AutoML ConsoleВидео
Reading: Cloud ML and AutoML Platform SetupЧтение
Practice Assignment : Cloud ML and AutoML Platform SetupЗадание

AutoML Tables for Structured Data

Data Preparation & Automated Feature EngineeringВидеоAutomated Model Selection, Training & EvaluationВидеоHands-On: Training Your First Classification Model with AutoML Tables (Web UI)ВидеоHands-On: Training Your First Regression Model with AutoML Tables (Web UI)ВидеоReading: AutoML Tables for Structured DataЧтениеPractice Assignment : AutoML Tables for Structured DataЗадание

Understanding Advanced ML Concepts with Demonstrations

Ensemble Learning & Gradient BoostingВидеоXGBoost - Optimized Gradient Boosting in PracticeВидеоExploring and Interpreting Ensemble Models in AutoML ReportsЧтениеDeep Learning & Neural Network FundamentalsВидеоConvolutional Neural Networks (CNNs)ВидеоRecurrent Neural Networks (RNNs)ВидеоHands-On: Interpreting Deep Neural Network Outputs in AutoML VisionВидеоHands-On: Analyzing CNN-Based Image Classification Results in AutoML VisionВидеоReading: Understanding Advanced ML Concepts with DemonstrationsЧтениеPractice Assignment: Understanding Advanced ML Concepts with DemonstrationsЗадание

Module Wrap-Up and Assessment

Module Summary: AutoML Platform Setup and Hands-On ExperienceЧтениеGraded Assignment: AutoML Platform Setup and Hands-On ExperienceЗаданиеAutoML Platform Setup & First Model LaunchDIALOGUE
02Advanced Model Training - Vision, NLP & RL Concepts17 материалов

Reinforcement Learning Concepts

Reinforcement Learning Fundamentals: Agents, Actions, Rewards and Q-LearningВидеоReal-World RL ApplicationsВидеоReading: Reinforcement Learning Concepts with DemonstrationsЧтениеPractice Assignment: Reinforcement Learning Concepts with DemonstrationsЗадание

AutoML Vision for Image Data

Computer Vision FundamentalsВидеоHands-On: Uploading Image Datasets and Labeling in AutoML VisionВидеоHands-On: Training Image Classification Models (Web UI)ВидеоHands-On: Training Object Detection Models and Evaluating ResultsВидеоReading: AutoML Vision for Image DataЧтениеPractice Assignment : AutoML Vision for Image DataЗадание

AutoML Natural Language for Text Data

NLP Fundamentals: Text Classification and Entity ExtractionВидеоHands-On: Training Text Classification and Sentiment Analysis Models (Web UI)ВидеоReading: AutoML Natural Language for Text DataЧтениеPractice Assignement: AutoML Natural Language for Text DataЗадание

Module Wrap-Up and Assessment

Module Summary: Advanced Model Training - Vision, NLP and RL ConceptsЧтениеGraded Assignment: Advanced Model Training - Vision, NLP & RL ConceptsЗаданиеAdvanced Model Training with Vision, NLP and RLDIALOGUE
03Model Deployment & Business Integration18 материалов

Deploying Models with AutoML

Model Deployment OptionsВидеоHands-On: Deploying Models for Online Predictions (Web UI)ВидеоHands-On: Making Predictions Using AutoML Console and Testing ModelsВидеоReading: Deploying Models with AutoMLЧтениеPractice Assignment : Deploying Models with AutoMLЗадание

No-Code Business Tool Integration

Integrating AutoML with Business ToolsВидеоHands-On: Connecting AutoML Predictions to Google Sheets (No-Code)ВидеоHands-On: Using BigQuery ML with AutoML for Data Analysis (UI Only)ВидеоReading: No-Code Business Tool IntegrationЧтениеPractice Assignment : No-Code Business Tool IntegrationЗадание

Monitoring and Managing Models

Model Monitoring: Performance Tracking and Model LifecycleВидеоHands-On: Monitoring Model Performance in Cloud ConsoleВидеоHands-On: Retraining Models with New Data in AutoML (Web UI)ВидеоReading: Monitoring and Managing ModelsЧтениеPractice Assignment: Monitoring and Managing ModelsЗадание

Module Wrap-Up and Assessment

Module Summary: Model Deployment and Business IntegrationЧтениеGraded Assignment: Model Deployment and Business IntegrationЗаданиеAutoML Deployment Strategy and Business IntegrationDIALOGUE
04Course Wrap-Up6 материалов

Course Wrap-up and Assessments

Final Checkpoint: Reflecting on No-Code AutoML & DeploymentDIALOGUEPractice Project: Building an End-to-End AutoML Intelligence System for NovaRetail GroupЧтениеKnowledge Check: Complete No-Code Advanced ML & Deployment JourneyЗаданиеEnterprise-Scale AutoML Implementation and Deployment StrategyЗаданиеEnterprise AutoML Transformation SimulationDIALOGUECourse SummaryВидео