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In this course, you will learn:
- How to set up an account and use the console, APIs, Cloud Shell, and other GCP tools. Then explore the core services—serverless computing, data storage, and machine learning—and the developer tools that Google provides for building your own custom solutions.
- Along the way, instructor Lynn Langit shows how to use GCP to manage virtual machines, Docker containers, Kubernetes clusters, functions, relational data stores, NoSQL data, and more.
Syllabus:
- Introduction
- Hosting your application on GCP
- What you should know
- A note about working with cloud services
1. Why Use the Google Cloud?
- Understanding Google Cloud Platform
- Save time and money with GCP
- Autoscale on GCP
- Compliance
- Service categories: Compute, data, and more
- Tools and libraries
2. Getting Started
- Set up Google Cloud Platform account
- Work with projects
- Use APIs
- Use regions and zones
- Understand Google Cloud billing
- Use Google Cloud Security/IAM
- Use integrated Google Cloud console
- Use local Google Cloud
3. Compute
- Google Compute Engine
- Google Compute Engine resources
- Google Cloud Functions
- App Engine
- Google Cloud Run
- Kubernetes Engine and GKE applications
- Kubernetes Engine and GKE cluster objects
- Anthos for Kubernetes
4. Storage and Database
- Google Cloud Storage
- Google Cloud SQL
- BigQuery
- GCP Marketplace data sets
- Cloud Bigtable
- Cloud Memorystore
- Cloud Firestore, formerly Cloud Datastore
- Cloud Pub/Sub
5. Machine Learning and Data Movement
- Cloud Dataprep
- Cloud Data Fusion
- Data Studio
- AI Platform and AI Hub
- Jupyter notebooks
- TensorFlow 2.0 in Colab notebooks
- Vision API
- Cloud AutoML Tables
- Data science VM
6. Developer Tools
- Deployment Manager and Marketplace
- Cloud Scheduler and Cloud Tasks
- Cloud Code
- Cloud Logging
- Continuous deployment with Cloud Build
7. Key Architectures
- GCP architecture concepts
- Web single-page and API-based architectures
- Web blog: Managed databases
- Mobile development with AI
- Big data log processing
