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Managing Cloud Infrastructure with Terraform

In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.

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Google Cloud Solutions I: Scaling Your Infrastructure

In this advanced-level quest, you will learn how you to harness serious GCP power and infrastructure. The hands-on labs will give you use cases, and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your GCP projects to the next level.

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Google Cloud Solutions II: Data and Machine Learning

In this advanced-level quest, you will learn how to harness serious GCP computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why GCP is the go-to platform for running big data and machine learning jobs.

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Stackdriver

In this fundamental-level quest, you will learn the ins and outs of Stackdriver: an important GCP service for generating insights into applications’ health. Stackdriver provides a wealth of information in application monitoring, report logging, and diagnoses. The labs in this quest will give you hands-on practice with Stackdriver, and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data.

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Machine Learning APIs

It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering it’s development. With a host of APIs, GCP has a tool for just about any machine learning job. In this advanced-level quest, you will get hands-on practice with machine learning APIs by taking labs like Implementing an AI Chatbot with Dialogflow and Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API.

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Cloud SQL

Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this fundamental-level quest, you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and highly available databases that run on GKE containers, Cloud SQL will give you the knowledge and experience needed so you can start integrating this service right away.

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Application Development - Python

In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.

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Application Development - Java

In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Java. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Java applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Java applications straight away.

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Network Performance and Optimization

If you want to take your GCP networking skills to the next level, look no further. This quest is composed of labs that cover real-life use cases and it will teach you best practices for overcoming common networking bottlenecks. From getting hands-on practice with testing and improving network performance, to integrating high-throughput VPNs and networking tiers, Network Performance and Optimization is an essential quest for GCP developers who are looking to double down on application speed and robustness.

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Scientific Data Processing

Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.

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