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

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AutoML: Build ML Models without Code

本课程是 No-Code Data Science and Machine Learning 专项课程的一部分

位教师：Edureka

包含在中

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4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

您将学到什么

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

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本课程是 No-Code Data Science and Machine Learning 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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该课程共有4个模块

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.

涵盖的内容

19个视频6篇阅读材料4个作业

19个视频总计84分钟

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

6篇阅读材料总计60分钟

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

4个作业总计33分钟

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

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.

涵盖的内容

8个视频4篇阅读材料4个作业

8个视频总计35分钟

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

4篇阅读材料总计40分钟

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

4个作业总计33分钟

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

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.

涵盖的内容

9个视频4篇阅读材料4个作业

9个视频总计37分钟

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

4篇阅读材料总计40分钟

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

4个作业总计33分钟

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

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.

涵盖的内容

1个视频1篇阅读材料2个作业

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常见问题

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.