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01

Build and Deploy Machine Learning Solutions on Vertex AI

01

Build and Deploy Machine Learning Solutions on Vertex AI

magic_button AutoML Vertex AI Managed Datasets Data Science Machine Learning Model Training
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2 hours 15 minutes Intermediate
Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.

Skill badges validate your practical knowledge on specific products through hands-on labs and challenge assessments. Earn a badge by completing a course or jump straight into the challenge lab to get your badge today. Badges prove your proficiency, enhance your professional profile, and ultimately lead to increased career opportunities. Visit your profile to track badges you’ve earned.

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Course Info
Objectives
  • Write and train models locally in a hosted Vertex Notebook.
  • Containerize your training code and push it to Google Cloud Artifact Registry.
  • Create managed image dataset artifacts for experiment tracking.
  • Train a BigQuery ML (BQML) XGBoost classifier.
  • Trigger a training job using the Vertex AI Console.
  • Create a custom model evaluation component using the KFP SDK.
  • Incorporate pre-built KFP components into your pipeline.
  • Deploy your trained models to a Vertex AI endpoint for online predictions.
  • Query your model for online predictions and explanations.
Prerequisites
Prior to enrolling in this skill badge course, it is recommended that you have prior experience with Python programming as covered in the Google Python Class and that you complete the Machine Learning Crash Course. See the Google Cloud Tech AI Simplified video series for an overview of Vertex AI.
Audience
This skill badge course is for professional Data Scientists and Machine Learning Engineers.
Available languages
English, Deutsch, bahasa Indonesia, português (Brasil), 日本語, 简体中文, 繁體中文, español (Latinoamérica), français ו한국어

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