Google’s cloud platform provides reliable and highly scalable infrastructure for developers to build, test and deploy apps.
It has lot of advantages over the competitors in the market like Higher Productivity, Less Disruption, Quick Collaboration and many more. It covers application, storage and computing services for backend, mobile and web solutions. More than four million apps trust and use the platform. Google tries to keep the backend as simple as possible and uses a simple file system. It handles requests for information via basic commands like write, read and open. It is a distributed system of computing.
- Resume & Interviews Preparation Support
- Hands on Experience on One Live Project.
- 100 % Placement Assistance
- Multiple Flexible Batches
- Missed Sessions Covered
- Practice Course Material
At the end of Google Cloud Platform Training Course, Participants will be able to:
- 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 Container 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
- 6 WEEKENDS
- Familiarity with application development, systems operations, Linux operating systems, and data analytics/machine learning is helpful in understanding the technologies covered.
Who Should Attend?
- 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.
1.1 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 1 Lab: Create a Google Cloud Platform project
1.2 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.
1.3 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
1.4 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
1.5 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
1.6 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
1.7 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
1.8 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
Classes are held on weekends. You can check available schedules and the batch timings.
Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certificate.