Foundational Data, ML, and AI Tasks in Google Cloud

Learn how to use Google Cloud’s powerful tools for foundational data, machine learning (ML), and artificial intelligence (AI) tasks.
Duration: 1 Day
Hours: 3 Hours
Training: Live Training
Training Level: All Level
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Friday, February 21, 2025
02:00 PM - 05:00 PM (Eastern Time)
Thursday, March 20, 2025
02:00 PM - 05:00 PM (Eastern Time)
Live Session
Single Attendee
$149.00 $249.00
Live Session
Recorded
Single Attendee
$199.00 $332.00
6 month Access for Recorded
Live+Recorded
Single Attendee
$249.00 $416.00
6 month Access for Recorded

About the Course:

This comprehensive 3-hour training session introduces participants to the foundational data processing, machine learning, and AI tasks in Google Cloud. We will explore essential tools such as BigQuery, Cloud Storage, Vertex AI, and AutoML to build and deploy intelligent solutions. Whether you're new to cloud technologies or looking to enhance your skills, this training will provide hands-on learning to navigate and leverage Google Cloud's powerful data, ML, and AI capabilities.

Course Objective:

  • Understand the core data storage and processing tools in Google Cloud (e.g., BigQuery, Cloud Storage).
  • Learn the foundational concepts and workflows in Machine Learning (ML) using Google Cloud.
  • Get hands-on experience with AutoML and Vertex AI to build, train, and deploy models.
  • Understand how to set up and manage AI pipelines, from data collection to model deployment.
  • Explore how Google Cloud integrates with existing data engineering and ML workflows.

Who is the Target Audience?

  • Data Engineers and Analysts
  • Machine Learning Engineers
  • AI/ML Enthusiasts
  • Developers and IT professionals looking to explore cloud-based AI solutions
  • Anyone interested in building or deploying ML models on Google Cloud

Basic Knowledge:

  • Familiarity with basic data concepts and storage.
  • Basic understanding of Machine Learning (ML) principles (e.g., supervised vs. unsupervised learning).
  • Basic experience with cloud computing (ideal but not required).
  • No prior experience with Google Cloud is necessary.

Curriculum
Total Duration: 3 Hours
Introduction to Google Cloud Platform (GCP) for Data, ML, and AI

  • Overview of GCP tools and services for data and machine learning  
  • GCP Console and project setup  

Google Cloud Storage & BigQuery

  • Cloud Storage for storing data at scale  
  • BigQuery for data processing and analytics  
  • Importing data into BigQuery and running queries  

Introduction to Machine Learning in Google Cloud

  • Understanding machine learning workflows  
  • Tools for ML on Google Cloud  
  • Overview of Vertex AI and AutoML services  

Building and Deploying Models with Vertex AI

  • Data preparation and feature engineering  
  • Training, tuning, and deploying models using Vertex AI  
  • Model monitoring and optimization  

Leveraging AutoML for Rapid ML Model Development

  • Introduction to AutoML tools  
  • Building custom models without deep ML expertise  
  • Training and evaluating AutoML models  

AI Pipelines and Automation

  • Creating and managing AI pipelines for reproducible ML workflows  
  • Using Vertex AI Pipelines and Workflow Automation in Google Cloud  

Real-world Use Cases and Best Practices

  • Common use cases for ML and AI in Google Cloud  
  • Best practices for data handling, model training, and deployment  

Q&A

  • Open forum for questions and discussion