GCP-INF: Google Cloud Fundamentals: Core Infrastructure


  • Duration: 3 Days
  • Mode of Delivery: Online -Instructor-led training
  • Level: Intermediate
  • Job role: Administrator
  • Preparation for exam: None
  • Cost: USD$1,800.00

Data management, data analytics, machine learning and artificial intelligence are all hot topics. And who does these better than Google? Our Google Certified Professional Data Engineer course will help prepare you for the certification exam so you can take that next step in your Cloud career and demonstrate your proficiency in one of the most in-demand disciplines in the industry today. The primary focus of this course is to prepare you for the GCP Professional Data Engineer certification exam. Along the way you’ll solidify your foundations in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.

20 in stock

SKU: AZ-303-1-1-2-2-1-1-1-1-1-1-1 Categories: , , , , ,


This course is intended for the following participants:
• Individuals planning to deploy applications and create application environments on Google Cloud Platform
• Developers, systems operations professionals, and solution architects getting started with Google Cloud Platform
• Executives and business decision makers evaluating the potential of Google Cloud Platform to address their business needs
• Creating and maintaining machine learning and statistical models
• Querying datasets, visualizing query results and creating reports


To get the most out of this course, you should be familiar with the Linux command line, web servers, and text editors.

Skills Gained

This course is intended for the following participants:
• Identify the purpose and value of Google Cloud Platform products and services
• Interact with Google Cloud Platform services
• Describe ways in which customers have used Google Cloud Platform
• Choose among and use application deployment environments on Google Cloud Platform: Google App Engine, Google Kubernetes Engine, and Google Compute Engine
• Choose among and use Google Cloud Platform storage options: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore
• Make basic use of BigQuery, Google’s managed data warehouse for analytics
• Make basic use of Cloud Deployment Manager, Google’s tool for creating and managing cloud resources through templates
• Make basic use of Google Stackdriver, Google’s monitoring, logging, and diagnostics system

Course outline

Module 1: Introducing Google Cloud Platform
• Explain the advantages of Google Cloud Platform
• 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)

Module 2: Getting Started with Google Cloud Platform
• Identify the purpose of projects on Google Cloud Platform
• Understand the purpose of and use cases for Identity and Access Management
• List the methods of interacting with Google Cloud Platform
• Lab: Getting Started with Google Cloud Platform

Module 3: Virtual Machines and Networks in the Cloud
• Identify the purpose of and use cases for Google Compute Engine
• Understand the various Google Cloud Platform networking and operational tools and services
• Lab: Compute Engine

Module 4: Storage in the Cloud
• Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore
• Learn how to choose between the various storage options on Google Cloud Platform
• Lab: Cloud Storage and Cloud SQL

Module 5: Containers in the Cloud
• Define the concept of a container and identify uses for containers
• Identify the purpose of and use cases for Google Kubernetes Engine and Kubernetes
• Lab: Kubernetes Engine

Module 6: Applications in the Cloud
• Understand the purpose of and use cases for Google App Engine
• Contrast the App Engine Standard environment with the App Engine Flexible environment
• Understand the purpose of and use cases for Google Cloud Endpoints
• Lab: App Engine

Module 7: Developing, Deploying, and Monitoring in the Cloud
• Understand options for software developers to host their source code
• Understand the purpose of template-based creation and management of resources
• Understand the purpose of integrated monitoring, alerting, and debugging
• Lab: Deployment Manager and Stackdriver

Module 8: Big Data and Machine Learning in the Cloud
• Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms
• Lab: BigQuery


Click on the following link to see the current Course Schedule
Our minimum class-size is 3 for this course.
If there are no scheduled dates for this course, it can be customized to suit the time and skill needs of clients and it can be held online, at a rented location or at your premises.
Click on the following link below to arrange for a custom course: Enquire about a course date

Product Information

The shift to the cloud is not a new thing, and for many years, companies have been utilizing cost-effective solutions from public cloud vendors to move away from traditional on-premises architecture. The speed at which technology is moving now makes it increasingly difficult for companies managing their own infrastructure to get the most out of their IT systems. Google has been developing its own tools to deliver services such as Gmail, YouTube, Google Drive, and Google+ for years. These tools have been converted into services that can be consumed by others. Consumers are given the amazing scalability that Google has to use for their own purposes. Google Cloud Platform (GCP) lets you choose from computing, storage, networking, big data, and machine learning (ML) services to build your application on top of them. The number of services is growing constantly, and new announcements are made on an almost weekly basis. New services and features are released, first as alpha then as beta versions, and finally, are made available globally. The early releases are available even earlier for selected customers and partners. This allows the services to be tested by external parties even before the official release.
We are given a variety of options when it comes to computing in GCP. Depending on our requirements and flexibility, we can choose from one of the following service models:
• Infrastructure as a Service (IaaS): Google Compute Engine (GCE)
• Container as a Service (CaaS): Google Kubernetes Engine (GKE)
• Platform as a Service (PaaS): Google App Engine (GAE)
• Function as a Service (FaaS): Cloud Functions

Additional Information and FAQs

CERTFICATE OF COMPLETION: Participants will receive a certificate of completion at the end of a course. This is not an official certification for the product and/or software. Our courses do indicate the appropriate certification exam(s) that the participant can sit. Data Vision Systems does not provide certification or deliver the certification exams. Participants are responsible for arranging and paying for the certification exams on the appropriate certification body.

CANCELLATION POLICY: There is never a fee for cancelling seven business days before a class for any reason. Data Vision Systems reserves the right to cancel any course due to insufficient registration or other extenuating circumstances. Participants will be advised prior to doing so.


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