Data Engineering on Google Cloud
Trainer: Zorro Cheng
Certificate: A minimum of 70% attendance rate is required for awarding of a completion certificate
Application Deadline: 7 days before the course
Remark: Please Bring your own laptop (BYOD) to classes.
What Will You Achieve
- Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services.
- Describe ways in which customers have used Google Cloud.
- Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine.
- Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore.
- Make basic use of BigQuery, Google’s managed data warehouse for analytics.
Who Is This Course For?
- Planned to deploy applications and create application environments on Google Cloud
- Developers, systems operations professionals, and solution architects getting started with Google Cloud
- Executives and business decision makers evaluating the potential of Google Cloud to address their business needs
Be familiar with
- Application Development
- Systems Operations
- Linux Operating systems,
- Data Analytics/Machine Learning
- Define the components of Google’s network infrastructure, including: Points of presence, data centers, regions, and zones.
- Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS).
- Understand the purpose of and use cases for Identity and Access Management and
- List the methods of interacting with GC.
- Lab: Getting Started with Cloud Marketplace.
- Identify the purpose of and use cases for Google Compute Engine and the basics of networking in GC.
- Lab: Getting Started with Google Compute Engine.
- Understand the purpose of and use cases for: Cloud Storage, Cloud Bigtable, Cloud SQL, Cloud Spanner, and Firestore.
- Learn how to choose between the various storage options on Google Cloud.
- Lab: Getting Started with Cloud Storage and Cloud SQL.
- Identify the purpose of and use cases for Google Kubernetes Engine and Kubernetes.
- Introduction to Hybrid and Multi-Cloud computing (Anthos).
- Lab: Getting Started with Kubernetes Engine.
- Contrast the App Engine standard environment with the App Engine flexible environment.
- Understand the purpose of and use cases for Cloud Endpoints.
- Lab: Getting Started with App Engine.
- Understand how Cloud Source Repositories, Cloud Functions, and Deployment Manager support development in the cloud.
- Understand the purpose of integrated monitoring, alerting, and debugging.
- Lab: Getting Started with Deployment Manager and Cloud Monitoring.
- Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms.
- Lab: Getting Started with BigQuery.