Google Cloud Fundamentals for Researchers
This 1-day course introduces researchers to the Google Cloud tools for working with research data.
Google Cloud Fundamentals for Researchers starts with interactive demos of research use cases, such as provisioning Compute Engine virtual machines, querying a billion rows of data in seconds in BigQuery and training a custom vision model with AutoML Vision. You then learn how resources, access and billing are organized in Google Cloud, how to store data in Cloud Storage buckets, provision virtual machines, understand computing costs and explore creating high-performance computing (HPC) clusters.
The course moves on to BigQuery, where you query public datasets, manage datasets and connect data to Looker Studio, and to notebooks on Agent Platform, where you provision Jupyter notebooks with Agent Platform Workbench and connect them to BigQuery for descriptive and predictive analysis. The course has six modules and five labs, including an optional lab deploying an HPC cluster with Slurm.
The course is for customers doing research on Google Cloud. Participants should have basic knowledge of data types and SQL, basic programming knowledge and an understanding of machine learning models such as supervised versus unsupervised models.