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Verified Information • Last Updated Mar 2026
AutoML: Build ML Models without Code
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.
Duration
4 Months
Institution
Edureka
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Edureka.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$271
Total Est. Investment
$271
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the AutoML: Build ML Models without Code program at Edureka are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.