1. INTRODUCTION TO GOOGLE CLOUD Data Engineer

 Understanding the fundamentals of Google Cloud Platform

 The Google global infrastructure

 Products for storage, compute, networking, Machine Learning, and more

 Availability zones

 Different projects running on the GCP infrastructure, including Google projects

 

2. GOOGLE CLOUD Data Prep

What is Data Prep

Cloud Dataprep by Trifacta is an intelligent data service for visually exploring, cleaning, and preparing data for analysis. Cloud Dataprep is serverless and works at any scale. 

We will use Dataprep to manipulate a dataset. You import datasets, correct mismatched data, transform data, and join data.

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3. Data Flow

 

Google DataFlow. We  will learn how to create a streaming pipeline using one of Google's Cloud Dataflow templates. More specifically, you will use the Cloud Pub/Sub to BigQuery template, which reads messages written in JSON from a Pub/Sub topic and pushes them to a BigQuery table. You can find the documentation for this template here.

 

 

4. DataProc

 

Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. Operations that used to take hours or days take seconds or minutes instead. Create Cloud Dataproc clusters quickly and resize them at any time, so you don't have to worry about your data pipelines outgrowing your clusters.

This lab shows you how to use the Google Cloud Console to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster.

 

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5. GOOGLE Cloud Natural Language API

 

 

6. GOOGLE Speech to Text API

 

 

7.Google Video Intelligence

 

 

8.Google AI Project

 Cloud Vision API

 

Project: AI Project with various Components:

We will deploy a AI Application built on Python Flask web application to the App Engine Flexible environment. 

The application allows a user to upload a photo of a person's face and learn how likely it is that the person is happy. 

The application uses Python code, Google App Engine Flexible, Google Cloud APIs for Vision, Storage, and Datastore/Firestore.