Do you want to start a career in cloud computing, but don’t know where to begin? If so, this course can help by providing an ideal foundational mapping of the career paths and certifications that IT professionals should consider if they’re interested in transitioning to cloud computing. Instructor and Cloud Architect Lynn Langit covers a variety of career paths, including IT pro, developer, analyst, and architect roles. Throughout the course, she focuses on the major cloud platforms—AWS, Microsoft Azure, Google, and the IBM Bluemix cloud with IBM Watson—discusses certifications available for each, and explores the future of cloud computing careers.

Topics include:

  • Reviewing IT pro, developer, analyst, and architect roles
  • Reviewing IT pro skills, including virtualization, networking, and scripting
  • Working with programming languages
  • Reviewing AWS, Azure, GCP, and IBM certifications
  • Reviewing cloud career paths
  • Understanding emerging technologies and careers

Table of Content



What you should know

A note about working with cloud services

1. What Is the Google Cloud Platform?

Cloud and compute services

Storage and data services

Big data services

Other services

2. Why Use the Google Cloud?

Save time and money with cloud services

Explore Google’s autoscaling and infrastructure

Understand Google’s compliance options

Get to know the personality of the Google Cloud Platform

Find helpful tools and libraries

3. Getting Started with the Google Cloud

Set up your account

Work with location and projects

Understand Google Cloud Billing

Use APIs

Use Google Cloud security: IAM

About gcloud

Set up command-line access with gcloud

Use walk-throughs and tutorials

Compare GCP to AWS

4. Using Google Compute Services

Understand Compute Service options

Use Google Compute Engine (GCE)

Use Cloud Launcher to set up an Eclipse Che IDE

Use GCE resources

Use Container Engine: GKE

Use Container Engine/GKE and Kubernetes, part 1

Use Container Engine/GKE and Kubernetes, part 2

Use Google App Engine

Understand Google Cloud functions

Understand Google Compute Services

5. Using Google Database and Storage Services

Understand storage and database options

Use Google Cloud Storage

Use the Google Cloud Storage JSON API

Use Google Cloud SQL

Use Google Cloud Datastore

Use Google Cloud Bigtable

Use Google BigQuery

Compare Bigtable to BigQuery

Understand Google Cloud Storage services

6. Using Google Data Pipeline Services

Understand data pipelines

Use Google Pub/Sub

Use Google Dataproc

Use Google Dataflow

Use the Google Genomics API

Understand Google Data Pipeline services

7. Using Google Machine Learning and Visualization

Understand Google Machine Learning and Viz

Use the Cloud Vision API

Use the Google Cloud Datalab

Use Datalab examples

Summarizing Machine Learning and Viz

8. Using Networking and Developer Tools

Understand networking and developer tools

Use Google Cloud networking services

Use Stackdriver Monitoring

Understand source code repositories

Summary of networking and developer tools

9. Implementing Solutions: Architectures and Practices

Use reference architectures

Disaster recovery architecture

Web/API application architectures

Big data and data warehouse

Internet of Things


Review your launch checklist

Explore some other resources


Next steps