Edureka

AutoML: Build ML Models without Code

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Edureka

AutoML: Build ML Models without Code

Edureka

Instructor: Edureka

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • 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

Details to know

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Assessments

14 assignments¹

AI Graded see disclaimer
Taught in English

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There are 4 modules in this course

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.

What's included

19 videos6 readings4 assignments

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.

What's included

8 videos4 readings4 assignments

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.

What's included

9 videos4 readings4 assignments

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.

What's included

1 video1 reading2 assignments

Instructor

Edureka
Edureka
152 Courses 141,395 learners

Offered by

Edureka

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.