Course Solutions

Find the right tools for your projects

There’s a lot you can do with Google Cloud Platform. Depending on the course you’re teaching or taking, you’ll need access to different products and resources. To help you find the right tool for you, we’ve organized this page around five key use cases: Deploying a Web Application, Gaining Insights Using Machine Learning APIs, Developing Your Own Machine Learning Models, Big Data, and Systems Administration. We encourage you to learn more about areas that interest you and your peers. These tutorials and codelabs will help get you started.

Deploying a web application

App Engine is a platform-as-a-service (PaaS) product that allows you to easily deploy your web applications without the hassle of managing servers— Google Cloud Platform handles management of most of your necessary computing resources for you instead. Several other important Google Cloud Platform products for web development include Cloud Storage, Datastore, and Google Cloud SQL.

Cloud Storage allows you to easily store and retrieve many types of files (like photos) for use in your application. Datastore is a highly-scalable NoSQL database that is easy to integrate into your applications. Google Cloud SQL is a fully-managed database service that makes it easy to setup, manage, and use relational databases on Google Cloud Platform.

App Engine

Cloud Storage


Gaining Insights Using Machine Learning APIs

Google Cloud Platform’s Machine Learning APIs use Google’s pre-trained machine learning models to give you insights for your video, image, speech, and text files.

Video Intelligence API

Vision API

Speech API

Natural Language API

Translate API

Developing Your Own Machine Learning Models

Google Cloud Machine Learning is a managed service that lets you build your own machine learning models using the TensorFlow framework. Knowledge of machine learning and TensorFlow is required for this product.

Cloud AutoML

Cloud ML Engine


Big Data

Google's mission is "To organize the world's information and make it universally accessible and useful,” so it should be no surprise it offers a variety of tools to help explore and process large amounts of data. Along with these tools, there are numerous public datasets that can be analyzed using BigQuery and SQL, including genomics datasets, US Census data, and 2016 Major League Baseball pitch activity.

Systems Administration

Sometimes you just want to use the GCP infrastructure as infrastructure. You can set up and administer virtual machines (VMs) and networks or explore DevOps. You can get experience administering a variety of different operating systems, create networks and subnets with different configurations, and practice for cyber-security competitions using GCP resources.

Virtual Machines


Monitoring and Logging

Automatic Deployment