Do I need to complete Courses 1 and 2 of the specialization first?

Yes, it is strongly recommended. This course assumes familiarity with data preparation concepts from Course 1 and core ML modeling principles from Course 2. Learners who skip these may find certain concepts harder to follow.

Is any coding required in this course?

No. All platform setup, dataset upload, model training, deployment, and monitoring is performed entirely through the Google Cloud web console — no terminal, CLI, or programming is involved at any point.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

AutoML: Build ML Models without Code

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

AutoML: Build ML Models without Code

Dieser Kurs ist Teil von Spezialisierung „No-Code Data Science and Machine Learning“

Dozent: Edureka

Bei enthalten

Mehr erfahren

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

8 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

8 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Set up Google Cloud Platform and Vertex AI to configure, upload datasets, and manage AutoML workflows for structured, image, and text data.
Train AutoML classification and regression models on structured data and interpret automated feature engineering and evaluation results
Build AutoML Vision and NLP models for image classification, object detection, and text sentiment analysis without writing any code
Deploy models for online predictions, connect outputs to Google Sheets and BigQuery, and monitor performance via the cloud console

Kompetenzen, die Sie erwerben

Kategorie: Google Cloud Platform
Kategorie: Machine Learning
Kategorie: Text Mining
Kategorie: Artificial Intelligence and Machine Learning (AI/ML)
Kategorie: Machine Learning Software
Kategorie: Computer Vision
Kategorie: Feature Engineering
Kategorie: Image Analysis
Kategorie: Applied Machine Learning
Kategorie: Cloud Deployment
Kategorie: Natural Language Processing
Kategorie: Predictive Modeling
Kategorie: Data Science
Kategorie: Model Evaluation

Werkzeuge, die Sie lernen werden

Kategorie: Model Deployment
Kategorie: Google Sheets
Kategorie: No-Code Development

Wichtige Details

Zertifikat zur Vorlage

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Kürzlich aktualisiert!

März 2026

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Unterrichtet in Englisch

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Dieser Kurs ist Teil der Spezialisierung Spezialisierung „No-Code Data Science and Machine Learning“

Wenn Sie sich für diesen Kurs anmelden, werden Sie auch für diese Spezialisierung angemeldet.

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Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
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In diesem Kurs gibt es 4 Module

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.

Build a strong foundation in cloud-based no-code machine learning by setting up and navigating Google Cloud and Vertex AI for AutoML workflows. Explore cloud ML architecture, platform components, and the business value of scalable AI systems. This module prepares you to confidently train and interpret AutoML models while understanding the core concepts powering automated intelligence.

Das ist alles enthalten

19 Videos6 Lektüren4 Aufgaben

19 Videos Insgesamt 84 Minuten

Course Introduction 3 Minuten
Cloud Machine Learning Platform Overview 5 Minuten
Benefits and Business Value of Cloud Machine Learning 6 Minuten
Platform Architecture and Workflow 5 Minuten
AutoML Capabilities and Features 5 Minuten
Hands-On: Configuring Google Cloud Platform for Machine Learning 5 Minuten
Hands-On: Setting Up Vertex AI Environment for AutoML Workflows 4 Minuten
Hands-On: Uploading and Managing Datasets in AutoML Console 3 Minuten
Data Preparation & Automated Feature Engineering 4 Minuten
Automated Model Selection, Training & Evaluation 4 Minuten
Hands-On: Training Your First Classification Model with AutoML Tables (Web UI) 4 Minuten
Hands-On: Training Your First Regression Model with AutoML Tables (Web UI) 6 Minuten
Ensemble Learning & Gradient Boosting 5 Minuten
XGBoost - Optimized Gradient Boosting in Practice 5 Minuten
Deep Learning & Neural Network Fundamentals 4 Minuten
Convolutional Neural Networks (CNNs) 4 Minuten
Recurrent Neural Networks (RNNs) 3 Minuten
Hands-On: Interpreting Deep Neural Network Outputs in AutoML Vision 6 Minuten
Hands-On: Analyzing CNN-Based Image Classification Results in AutoML Vision 4 Minuten

6 Lektüren Insgesamt 60 Minuten

Course Outline: Complete No-Code Advanced ML & Deployment Journey 10 Minuten
Reading: Cloud ML and AutoML Platform Setup 10 Minuten
Reading: AutoML Tables for Structured Data 10 Minuten
Exploring and Interpreting Ensemble Models in AutoML Reports 10 Minuten
Reading: Understanding Advanced ML Concepts with Demonstrations 10 Minuten
Module Summary: AutoML Platform Setup and Hands-On Experience 10 Minuten

4 Aufgaben Insgesamt 33 Minuten

Practice Assignment : Cloud ML and AutoML Platform Setup 6 Minuten
Practice Assignment : AutoML Tables for Structured Data 6 Minuten
Practice Assignment: Understanding Advanced ML Concepts with Demonstrations 6 Minuten
Graded Assignment: AutoML Platform Setup and Hands-On Experience 15 Minuten

Advance your modeling capabilities by working with image, text, and reinforcement learning concepts using AutoML Vision and AutoML Natural Language. Learn to train image classification and object detection models, build sentiment analysis and text classification systems, and interpret performance metrics responsibly. By the end of this module, you will be able to select the right AutoML solution for diverse data types and align advanced AI techniques with practical business use cases.

Das ist alles enthalten

8 Videos4 Lektüren4 Aufgaben

8 Videos Insgesamt 35 Minuten

Reinforcement Learning Fundamentals: Agents, Actions, Rewards and Q-Learning 5 Minuten
Real-World RL Applications 4 Minuten
Computer Vision Fundamentals 5 Minuten
Hands-On: Uploading Image Datasets and Labeling in AutoML Vision 3 Minuten
Hands-On: Training Image Classification Models (Web UI) 5 Minuten
Hands-On: Training Object Detection Models and Evaluating Results 3 Minuten
NLP Fundamentals: Text Classification and Entity Extraction 4 Minuten
Hands-On: Training Text Classification and Sentiment Analysis Models (Web UI) 5 Minuten

4 Lektüren Insgesamt 40 Minuten

Reading: Reinforcement Learning Concepts with Demonstrations 10 Minuten
Reading: AutoML Vision for Image Data 10 Minuten
Reading: AutoML Natural Language for Text Data 10 Minuten
Module Summary: Advanced Model Training - Vision, NLP and RL Concepts 10 Minuten

4 Aufgaben Insgesamt 33 Minuten

Practice Assignment: Reinforcement Learning Concepts with Demonstrations 6 Minuten
Practice Assignment : AutoML Vision for Image Data 6 Minuten
Practice Assignement: AutoML Natural Language for Text Data 6 Minuten
Graded Assignment: Advanced Model Training - Vision, NLP & RL Concepts 15 Minuten

Complete the end-to-end machine learning lifecycle by deploying, integrating, and managing models in production environments. Learn to choose between online and batch prediction strategies based on business requirements and performance constraints. Integrate AutoML outputs with tools like Google Sheets and BigQuery to operationalize insights in real workflows. This module equips you to move beyond experimentation and build scalable, production-ready AI systems that deliver measurable business value.

Das ist alles enthalten

9 Videos4 Lektüren4 Aufgaben

9 Videos Insgesamt 37 Minuten

Model Deployment Options 4 Minuten
Hands-On: Deploying Models for Online Predictions (Web UI) 4 Minuten
Hands-On: Making Predictions Using AutoML Console and Testing Models 4 Minuten
Integrating AutoML with Business Tools 4 Minuten
Hands-On: Connecting AutoML Predictions to Google Sheets (No-Code) 4 Minuten
Hands-On: Using BigQuery ML with AutoML for Data Analysis (UI Only) 5 Minuten
Model Monitoring: Performance Tracking and Model Lifecycle 4 Minuten
Hands-On: Monitoring Model Performance in Cloud Console 4 Minuten
Hands-On: Retraining Models with New Data in AutoML (Web UI) 5 Minuten

4 Lektüren Insgesamt 40 Minuten

Reading: Deploying Models with AutoML 10 Minuten
Reading: No-Code Business Tool Integration 10 Minuten
Reading: Monitoring and Managing Models 10 Minuten
Module Summary: Model Deployment and Business Integration 10 Minuten

4 Aufgaben Insgesamt 33 Minuten

Practice Assignment : Deploying Models with AutoML 6 Minuten
Practice Assignment : No-Code Business Tool Integration 6 Minuten
Practice Assignment: Monitoring and Managing Models 6 Minuten
Graded Assignment: Model Deployment and Business Integration 15 Minuten

Consolidate your learning by revisiting the complete no-code AutoML lifecycle, from cloud platform setup and structured data modeling to advanced Vision, NLP, and reinforcement learning concepts. Reinforce key ideas in model training, evaluation, deployment strategies, business integration, and lifecycle management while demonstrating your ability to design, deploy, and monitor end-to-end machine learning solutions using Google Cloud Vertex AI through a comprehensive final assessment.

Das ist alles enthalten

1 Video1 Lektüre2 Aufgaben

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Dozent

Edureka

157 Kurse 145.837 Lernende

von

Edureka

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Häufig gestellte Fragen

AutoML automates the machine learning pipeline — including data preprocessing, feature engineering, model selection, and hyperparameter tuning — enabling anyone to build production-grade ML models without deep technical expertise or code.

Google Vertex AI is Google Cloud's unified ML platform that brings AutoML and custom ML tools together in one place. In this course, you'll use Vertex AI's AutoML capabilities entirely through the web-based console — no command-line or API usage required.

Ideal for data analysts, product managers, business intelligence professionals, domain experts, and non-technical teams who want to leverage cloud-based ML to automate predictions and integrate AI into real business workflows.

Every platform task — from configuring Vertex AI to training and deploying models — is demonstrated step-by-step in instructor-led videos recorded directly in the Google Cloud console. You're expected to set up your own Google Cloud account, follow along with the instructor in real time, and pause the video whenever you need to complete a step, review a configuration, or wait for a model training job to finish.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

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¹ Einige Aufgaben in diesem Kurs werden mit AI bewertet. Für diese Aufgaben werden Ihre Daten in Übereinstimmung mit Datenschutzhinweis von Courseraverwendet.