Google Cloud Skills Boost

Build and Deploy Machine Learning Solutions on Vertex AI

8 hours Advanced universal_currency_alt 35 Credits
Earn a skill badge by completing the Build and Deploy Machine Learning Solutions with Vertex AI quest, where you will learn how to use Google Cloud’s unified Vertex AI platform and its AutoML and custom training services to train, evaluate, tune, explain, and deploy machine learning solutions.

This lab series is for professional Data Scientists and Machine Learning Engineers. The datasets and labs are built around high business impact enterprise machine learning use cases; these include retail customer lifetime value prediction, mobile game churn prediction, visual car part defection identification, and fine tuning BERT for review sentiment classification. Learners who complete this skill badge will gain hands-on experience with Vertex AI for new and existing ML workloads and be able to leverage AutoML, custom training, and new MLOps services to significantly enhance development productivity and accelerate time to value.

A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

When you complete this activity, you can earn the badge displayed above! View all the badges you have earned by visiting your profile page. Boost your cloud career by showing the world the skills you have developed!

  • Lab

    Vertex AI: Qwik Start

    In this lab, you will use BigQuery for data processing and exploratory data analysis, and the Vertex AI platform to train and deploy a custom TensorFlow Regressor model to predict customer lifetime value (CLV). The goal of the lab is to introduce to Vertex AI through a high value real world use case - predictive CLV. Starting with a local BigQuery and TensorFlow workflow, you will progress toward training and deploying your model in the cloud with Vertex AI.

  • Lab

    Identify Damaged Car Parts with Vertex AutoML Vision

    In this lab, you will learn how to train a custom Vertex AI image classification model to recognize damaged car parts.

  • Lab

    Deploy a BigQuery ML Customer Churn Classifier to Vertex AI for Online Predictions

    In this lab, you will train, tune, evaluate, explain, and generate batch and online predictions with a BigQuery ML XGBoost model. You will use a Google Analytics 4 dataset from a real mobile application, Flood it!, to determine the likelihood of users returning to the application. You will generate batch predictions with your BigQuery ML model as well as export and deploy it to Vertex AI for online predictions.

  • Lab

    Vertex Pipelines: Qwik Start

    In this lab you will create ML Pipelines using Vertex AI

  • Lab

    warning Building and Deploying Machine Learning Solutions with Vertex AI: Challenge Lab

    In this challenge lab you will train, deploy, and create a model pipeline using Vertex AI.

  • info
    Quest Info
    Prerequisites
    This skill badge assumes working proficiency with Python programming to utilize the Vertex AI Python SDK, and knowledge of topics covered in the or , and you have prior understanding of foundational Machine Learning topics as covered in the .
    Available languages
    English
    What do I do when I finish this quest?
    After finishing this quest, you can explore additional content in your learning path or browse the learning catalog.
    What badges can I earn?
    Upon finishing a quest, you will earn a badge of completion. Some quests test your ability to apply your knowledge via a final assessment challenge lab. For these quests, you will receive a skill badge. Badges can be viewed on your profile and shared with your social network.