[RTTP] Data Engineering on Google Cloud

TBC

09:30 – 17:30

(Total 32 hours)

Cantonese, Supplemented with English terminology

HK$40,000

Course Information

Course Name:

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

Requirement

Be familiar with

  • Application Development
  • Systems Operations
  • Linux Operating systems,
  • Data Analytics/Machine Learning

Course Outline

  • 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.

Application Form

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