T-GCFR-BOfficial Google Curriculum
Google Cloud Fundamentals for Researchers
1 dayILTIntroductory0
Overview
Learn how to use various tools in Google Cloud to ingest, manage and leverage your data to derive insights in your research.
What You'll Learn
- Understand products available in Google Cloud for research
- Load unstructured and structured data into Google Cloud
- Manage access and sharing your data on Google Cloud
- Understand costs on Google Cloud
- Leverage Jupyter Notebook environments in Vertex AI Workbench
- Utilize machine learning solutions on Google Cloud
Who Should Attend
Customers
Prerequisites
Basic knowledge of data types and SQL; Basic programming knowledge; Machine learning models such as supervised versus unsupervised models
Products Covered
Compute EngineCloud StorageBigQueryLooker StudioVertex AI WorkbenchVertex AI AutoML
Course Modules
1
Google Cloud Demos for Researchers
Topics
- 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
Learning Outcomes
- Explore research use cases in Google Cloud through interactive demos.
2
Google Cloud Project Concepts
Topics
- Organizing resources in Google Cloud
- Controlling Access to projects and resources
- Cost and billing management
Learning Outcomes
- Understand how resources in Google Cloud are managed across organizations, folders and projects.
- Control access to projects and resources using IAM
- Explore billing in Google Cloud
3
Computing and Storage in Google Cloud
Topics
- Interacting with Google Cloud
- Create and Manage Cloud Storage Buckets
- Compute Engine virtual machines
- Understanding computing costs
- Introduction to HPC on Google Cloud
Learning Outcomes
- Understand the methods of interacting with Google Cloud
- Store your data in Cloud Storage buckets
- Provision Compute Engine virtual machines
- Understand computing costs on Google Cloud
- Explore how you can create HPC clusters on Google Cloud
Activities
Lab: Create and Manage a Virtual Machine (Linux) and Cloud StorageOptional Lab: Deploy an HPC Cluster with Slurm
4
BigQuery
Topics
- BigQuery fundamentals
- Querying public datasets
- Importing and exporting data in BigQuery
- Connecting to Looker Studio
Learning Outcomes
- Understand the fundamentals of BigQuery
- Query public datasets in BigQuery Studio
- Manage datasets in BigQuery
- Connect data in BigQuery to Looker Studio
Activities
Lab: BigQuery and Looker Studio Fundamentals
5
Notebooks on Vertex AI
Topics
- Vertex AI
- Vertex AI Workbench
- Connecting Jupyter notebooks to BigQuery
Learning Outcomes
- Explore Vertex AI as a machine learning platform
- Provision Jupyter notebooks using Vertex AI Workbench
Activities
Lab: Interacting with BigQuery using Python and R Running in Jupyter Notebooks
6
Machine Learning on Google Cloud
Topics
- ML Options on Google Cloud
- Prebuilt ML APIs
- Vertex AI AutoML
- BigQuery ML
Learning Outcomes
- Explore machine learning options on Google Cloud
- Understand unstructured data using prebuilt ML APIs
- Create no-code custom ML models using Vertex AI AutoML
- Create custom ML models using SQL on BigQuery ML
Activities
Optional Lab: Extract, Analyze, and Translate Text from Images with the Cloud ML APIsOptional Lab: Identify Damaged Car Parts with Vertex AutoML VisionOptional Lab: Getting Started with BigQuery Machine Learning
Get This Training
No public classes currently scheduled. Express interest below or request private training.
Course Details
- Course Code
- T-GCFR-B
- Duration
- 1 day
- Format
- ILT
- Level
- Introductory
- Modules
- 6
- Activities
- 5
Questions About This Course?
Contact us for custom scheduling, group discounts, or curriculum customization.
Contact UsFree