OpenCourser brand icon
Sign in
We may earn an affiliate commission when you visit our partners.
Course image
Course image
Coursera logo

Identify Damaged Car Parts with Vertex AutoML Vision

Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console.

Vertex AI brings together the Google Cloud services for building ML under one, unified UI and API. In Vertex AI, you can now easily train and compare models using AutoML or custom code training and all your models are stored in one central model repository. These models can now be deployed to the same endpoints on Vertex AI.

Read more

This is a self-paced lab that takes place in the Google Cloud console.

Vertex AI brings together the Google Cloud services for building ML under one, unified UI and API. In Vertex AI, you can now easily train and compare models using AutoML or custom code training and all your models are stored in one central model repository. These models can now be deployed to the same endpoints on Vertex AI.

AutoML Vision helps anyone with limited Machine Learning (ML) expertise train high quality image classification models. In this hands-on lab, you will learn how to produce a custom ML model that automatically recognizes damaged car parts.

Once you’ve produced your ML model, it’ll be immediately available for use. You can use the UI or the REST API to start generating predictions directly from the Google Cloud Console.

Enroll now

Here's a deal for you

Save money when you learn with a deal that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until March 12, 2027
Save 40% Off 3 Months
Access thousands of top-rated learning programs with a Coursera Plus monthly subscription and take 40% off 3 months for a limited time.
Take
40%
off
Get offer

What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Develops skills in using Google Cloud services for building Machine Learning (ML) models
Explores AutoML Vision, a tool that makes it easy for users with limited ML expertise to train image classification models
Provides hands-on labs for practical application of ML techniques
Introduces Vertex AI, a unified platform for ML development, training, and deployment
Taught by Google Cloud Training, an organization recognized for its expertise in cloud computing and ML

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Practical damaged car part detection with automl

According to students, this course provides a practical, hands-on introduction to using Google Cloud's Vertex AI AutoML Vision for image classification. Learners appreciate the clear, step-by-step guidance in building a model to identify damaged car parts, making complex machine learning concepts accessible. While the hands-on lab environment is a significant strength, some suggest a basic understanding of machine learning concepts or Python could enhance the learning experience, as the course primarily focuses on the tool's application rather than foundational ML theory. Overall, it's considered a valuable experience for those looking to apply AutoML in a real-world scenario.
Independent learning with limited direct support.
"Being self-paced was great for my schedule, but I missed having an instructor for immediate questions."
"I could learn at my own speed, which was perfect, though I had to rely on documentation for troubleshooting."
"The lack of direct instructor support means I had to figure out some minor issues on my own."
Explores a very specific, practical application.
"The focus on identifying damaged car parts was highly relevant to my industry, but might be too specific for others."
"I found the practical example useful, though I wish there were mentions of how to generalize it to other image types."
"This lab provides a concrete example, showing exactly how to use the tool for a specific problem."
Makes complex machine learning accessible to many.
"As someone with limited ML expertise, I found AutoML Vision surprisingly easy to use for classification tasks."
"This course successfully demonstrated how to leverage powerful ML tools without becoming an expert in algorithms."
"I learned that even without extensive coding, I could train a high-quality image classification model."
Focuses on direct application of Vertex AI in a lab.
"I really valued the hands-on approach and being able to work directly in the Google Cloud console."
"The lab provides excellent practical experience in building an ML model without needing deep coding knowledge."
"I appreciate how I could immediately apply Vertex AutoML Vision to a real-world problem."
Benefits from prior understanding of core ML concepts.
"While AutoML reduces complexity, I think a basic understanding of what ML models do was very helpful."
"I found myself looking up some ML terms, suggesting a small pre-requisite might be beneficial for true beginners."
"It was easier to follow having some familiarity with machine learning workflows, even if not coding them."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Identify Damaged Car Parts with Vertex AutoML Vision with these activities:
Review Image Processing Techniques
Brush up on image processing techniques to enhance your understanding of the image classification process used in AutoML Vision.
Browse courses on Image Processing
Show steps
  • Read articles or books on basic image processing concepts.
  • Complete online courses or tutorials on image processing.
  • Experiment with image processing libraries or tools.
Review Machine Learning Concepts
Review the fundamentals of machine learning to ensure a strong foundation for the course.
Browse courses on Machine Learning
Show steps
  • Read introductory articles or textbooks on machine learning concepts.
  • Complete online tutorials or courses on machine learning basics.
  • Practice implementing simple machine learning algorithms in a programming language.
Attend an AutoML Vision Workshop
Accelerate your learning by attending a workshop or webinar focused on AutoML Vision.
Show steps
  • Research and identify upcoming AutoML Vision workshops or webinars.
  • Register for and attend the workshop or webinar.
  • Actively participate in the workshop or webinar, ask questions, and take notes.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore Vertex AI Documentation
Familiarize yourself with the Vertex AI platform by exploring its documentation.
Show steps
  • Visit the Vertex AI documentation website.
  • Read through the tutorials and guides for AutoML Vision.
  • Experiment with the code samples provided in the documentation.
Participate in Discussion Forums
Engage with other learners by participating in online discussion forums related to the course content.
Show steps
  • Join online discussion forums or communities related to machine learning or AutoML Vision.
  • Ask questions, share insights, and engage in discussions with other participants.
  • Seek support and guidance from experienced individuals in the community.
Create a Custom Image Classification Model
Gain hands-on experience by creating a custom image classification model using AutoML Vision.
Show steps
  • Gather a dataset of images for the desired classification task.
  • Upload the dataset to the Vertex AI platform.
  • Create an AutoML Vision model and train it on the dataset.
  • Evaluate the performance of the model and make adjustments as needed.
Organize and Review Course Materials
Stay organized and enhance your learning by compiling and reviewing course materials regularly.
Show steps
  • Create a system for organizing notes, assignments, and other course materials.
  • Review your notes and materials periodically to reinforce your understanding.
  • Summarize key concepts and ideas from the course materials.
Build a Web Application to Deploy the Model
Apply your knowledge by building a web application that uses the trained model to classify images.
Show steps
  • Design the architecture of the web application.
  • Develop the front-end and back-end components.
  • Integrate the AutoML Vision model into the application.
  • Test and deploy the web application.

Career center

Learners who complete Identify Damaged Car Parts with Vertex AutoML Vision will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers design, implement, and maintain machine learning systems. This course may be useful to Machine Learning Engineers as it provides them with the skills to train and deploy a custom ML model that can be used to identify damaged car parts. This can help Machine Learning Engineers to develop new products and services that can improve the safety and efficiency of the automotive industry.
See salaries and explore the career path for Machine Learning Engineer
Automotive Engineer
Automotive Engineers design, develop, and test vehicles and their components. This course may be useful to Automotive Engineers as it provides them with the skills to use machine learning to improve the safety and efficiency of vehicles. This can help Automotive Engineers to develop new technologies that can benefit the automotive industry and the public at large.
See salaries and explore the career path for Automotive Engineer
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful to Data Scientists as it provides them with the skills to train and deploy a custom ML model that can be used to identify damaged car parts. This can help Data Scientists to develop new products and services that can improve the safety and efficiency of the automotive industry.
See salaries and explore the career path for Data Scientist
Research Scientist
Research Scientists conduct research and development in various scientific and technological fields. This course may be useful to Research Scientists as it provides them with the skills to develop new machine learning algorithms and models. This can help Research Scientists to advance the field of machine learning and develop new technologies that can benefit society.
See salaries and explore the career path for Research Scientist
Software Developer
Software Developers design, develop, and maintain software applications. This course may be useful to Software Developers as it provides them with the skills to develop and deploy a custom ML model. This can help Software Developers to create new software applications that can improve the safety and efficiency of the automotive industry.
See salaries and explore the career path for Software Developer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful to Software Engineers as it provides them with the skills to develop and deploy a custom ML model. This can help Software Engineers to create new software systems that can improve the safety and efficiency of the automotive industry.
See salaries and explore the career path for Software Engineer
Manufacturing Engineer
Manufacturing Engineers design and manage the production of goods and services. This course may be useful to Manufacturing Engineers as it provides them with the skills to use machine learning to improve the efficiency of their manufacturing processes. This can help Manufacturing Engineers to reduce costs and improve the quality of their products.
See salaries and explore the career path for Manufacturing Engineer
Product Manager
Product Managers are responsible for the development and launch of new products and services. This course may be useful to Product Managers as it provides them with the skills to identify and assess the needs of their customers. This can help Product Managers to develop products and services that are in high demand and that meet the needs of the market.
See salaries and explore the career path for Product Manager
Quality Assurance Analyst
Quality Assurance Analysts test and evaluate software products to ensure that they meet the required standards. This course may be useful to Quality Assurance Analysts as it provides them with the skills to assess the accuracy and reliability of a custom ML model. This can help Quality Assurance Analysts to ensure that the software products they are testing are of the highest quality possible.
See salaries and explore the career path for Quality Assurance Analyst
Project Manager
Project Managers plan, organize, and manage projects. This course may be useful to Project Managers as it provides them with the skills to manage the development and deployment of a custom ML model. This can help Project Managers to ensure that their projects are completed on time, within budget, and to the required specifications.
See salaries and explore the career path for Project Manager
Solutions Architect
Solutions Architects design and implement technical solutions to meet the needs of their customers. This course may be useful to Solutions Architects as it provides them with the skills to assess the needs of their customers and develop solutions that meet those needs. This can help Solutions Architects to develop successful solutions that meet the business objectives of their customers.
See salaries and explore the career path for Solutions Architect
Technical Writer
Technical Writers create and maintain technical documentation. This course may be useful to Technical Writers as it provides them with the skills to communicate complex technical information in a clear and concise manner. This can help Technical Writers to create documentation that is easy to understand and use.
See salaries and explore the career path for Technical Writer
User Experience Designer
User Experience Designers design and evaluate user interfaces for software products. This course may be useful to User Experience Designers as it provides them with the skills to assess the needs of their users and design interfaces that are easy to use and understand. This can help User Experience Designers to create software products that are enjoyable and efficient to use.
See salaries and explore the career path for User Experience Designer
Data Engineer
Data Engineers design, construct, and maintain data management systems. This course may be useful to Data Engineers as it provides them with the skills to build a custom ML model that can be used to automate the process of identifying damaged car parts. This can help Data Engineers to improve the efficiency of their data management systems and free up their time to focus on other tasks.
See salaries and explore the career path for Data Engineer
Data Analyst
Data Analysts translate raw data into usable information using statistical analysis and software. This course may be useful to Data Analysts as it provides them with the skills to assess the accuracy of their data through the training of an ML model. This is useful for making sure that the data used by Data Analysts is of the highest quality possible, leading to more accurate and actionable insights.
See salaries and explore the career path for Data Analyst

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Identify Damaged Car Parts with Vertex AutoML Vision.
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a comprehensive overview of machine learning concepts and techniques, using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers various aspects of machine learning, including data preprocessing, feature engineering, model selection, and evaluation.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Deep Learning with Python, Second Edition
Save
Focuses on deep learning, a subfield of machine learning that uses artificial neural networks. It provides a practical guide to building and training deep learning models using Python libraries such as Keras and TensorFlow.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
Computer Vision
Save
Provides a comprehensive overview of computer vision algorithms and applications. It covers various aspects of computer vision, including image processing, object detection, and image recognition.
Computer Vision
Paperback
Check
Computer Vision
Kindle Edition
Check
Cover image
The Elements of Statistical Learning
Save
Provides a comprehensive overview of statistical learning methods. It covers various topics such as linear regression, logistic regression, decision trees, and support vector machines.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Machine Learning Con Pytorch Y Scikit Lean
Save
Provides a comprehensive overview of machine learning in Python. It covers various aspects of machine learning, including data preprocessing, feature engineering, model selection, and evaluation.
(Español) Machine Learning con PyTorch y Scikit-Learn:...
Paperback
$$$
Cover image
Machine Learning with R
Save
Covers machine learning concepts and techniques using the R programming language. It provides a practical guide to building and training machine learning models using R libraries such as caret and mlr.
Machine Learning with R - Fourth Edition: Learn...
Paperback
$$
Machine Learning with R - Second Edition: Expert...
Kindle Edition
$$
Machine Learning with R - Third Edition: Expert...
Paperback
$$
(Italiano) Machine Learning con R: Conoscere le tecniche per...
Kindle Edition
$$
R: Unleash Machine Learning Techniques
Kindle Edition
$$$
Machine Learning with R: Learn How to Use R to...
Paperback
$$
(中文) Machine learning and R language (3rd edition of the...
Paperback
$$
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive overview of natural language processing (NLP) in Python. It covers various aspects of NLP, including text preprocessing, text classification, and sentiment analysis.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
Data Science from Scratch
Save
Provides a practical introduction to data science using Python. It covers various aspects of data science, including data cleaning, data exploration, and machine learning.
Data Science from Scratch: First Principles with...
Paperback
$$
Data Science from Scratch: First Principles with...
Kindle Edition
$$
Data Science from Scratch: First Principles with...
Paperback
$$
Cover image
Deep Learning for Natural Language Processing
Save
Provides a gentle introduction to machine learning concepts and algorithms. It covers the basics of machine learning, including supervised and unsupervised learning, regression, and classification.
Deep Learning for Natural Language Processing
Paperback
Check
Deep Learning for Natural Language Processing
Kindle Edition
Check
Cover image
Machine Learning for Hackers
Save
Provides a practical introduction to machine learning for non-technical readers. It covers the basics of machine learning, including supervised and unsupervised learning, regression, and classification.
Machine Learning for Hackers: Case Studies and...
Paperback
$$
Machine Learning for Hackers: Case Studies and...
Kindle Edition
$$

Share

Help others find this course page by sharing it with your friends and followers:
Facebook
LinkedIn
Reddit
X
Link
Email

Similar courses

Here are nine courses similar to Identify Damaged Car Parts with Vertex AutoML Vision.
AI in Healthcare Capstone
Most relevant
Machine Learning Under the Hood: The Technical Tips,...
Most relevant
Probabilistic Deep Learning with TensorFlow 2
Most relevant
GenAI for Data Science Teams
Most relevant
Amazon Kendra Getting Started
Most relevant
GenAI Chatbots: Create and Deploy OpenAI-Powered Chatbots
Most relevant
The Art & Science of Product Management
Most relevant
Tweet Emotion Recognition with TensorFlow
Most relevant
Launching Machine Learning: Delivering Operational...
Most relevant

Coursera Buyer Protection & Guarantee

Verified partner policies & purchase protections

Accredited University Partner
Free Trial & Audit

7-Day Free Trial & Free Audit

7-day free trial on monthly Coursera Plus subscriptions; free audit option available on most individual courses to explore video lectures and readings at no charge.

Return & Refund Policy

14-Day Refund Guarantee

14-day refund window on annual Coursera Plus subscriptions and single-course purchases prior to certificate issuance. Monthly subscriptions do not offer refunds once billed.

Buyer Protections

Verified Academic & Industry Partner

Accredited university and industry certifications (e.g. Stanford, Google, IBM, Yale), secure SSL payment processing, and verifiable digital certificate links.

Key Purchase Protections
14-day refund window on annual Coursera Plus and single courses
7-day free trial on monthly Coursera Plus subscriptions
Free course audit option for lectures and readings
Verified certificates from top universities & companies
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Course image
Effort
1 hour 30 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Develops skills in using Google Cloud services for building Machine Learning (ML) models
Explores AutoML Vision, a tool that makes it easy for users with limited ML expertise to train image classification models
Provides hands-on labs for practical application of ML techniques
Introduces Vertex AI, a unified platform for ML development, training, and deployment
Taught by Google Cloud Training, an organization recognized for its expertise in cloud computing and ML
Share this
Share to help others discover this course.
Facebook LinkedIn X Reddit Link Email
Begin learning today
Enroll now to gain full access to Identify Damaged Car Parts with Vertex AutoML Vision.
Enroll now
Save for later
Add this course to your list. Find it anytime.
Save
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser