Google Cloud Fundamentals for Researchers (GCFR) – Outline

Outline detalhado do curso

Module 1 - Google Cloud Demos for Researchers

  • Demo: Provision Compute Engine virtual machines
  • Demo: Query a billion rows of data in seconds using BigQuery
  • Demo: Train a custom vision model using AutoML Vision

Module 2 - Google Project Concepts

  • Organizing resources in Google Cloud
  • Controlling Access to projects and resources
  • Cost and billing management

Module 3 - Computing and Storage on Google Cloud

  • Interacting with Google Cloud
  • Create and Manage Cloud Storage Buckets
  • Compute Engine virtual machines
  • Understanding computing costs
  • Introduction to HPC on Google Cloud
  • Lab 1: Create and Manage a Virtual Machine (Linux) and Cloud Storage

Module 4 - BigQuery

  • BigQuery fundamentals
  • Querying public datasets
  • Importing and exporting data in BigQuery
  • Connecting to Looker Studio
  • Lab 3: BigQuery and Looker Studio Fundamentals

Module 5 - Vertex AI Notebooks

  • Enabling APIs and services
  • Vertex AI
  • Vertex Workbench
  • Connecting Jupyter notebooks to BigQuery
  • Lab 4: Interacting with BigQuery using Python and R Running in Jupyter Notebooks

Module 6 - Machine Learning

  • Types of ML within Google Cloud
  • Prebuilt ML APIs
  • Vertex AI AutoML
  • BigQuery ML
  • Lab 5: Optional (take-home) labs to choose from:
    • Extract, Analyze, and Translate Text from Images with the Cloud ML APIs
    • Identify Damaged Car Parts with Vertex AutoML Vision
    • Getting Started with BigQuery Machine Learning