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GCP: Complete Google Data Engineer and Cloud Architect Guide

You, This Course and Us :
You, This Course and Us
Important! Delete unused GCP projects/instances
Course Materials

Introduction :
Theory, Practice and Tests
Why Cloud?
Hadoop and Distributed Computing
On-premise, Colocation or Cloud?
Introducing the Google Cloud Platform
Lab: Setting Up A GCP Account
Lab: Using The Cloud Shell
GCP Introduction
9 questions

Compute Choices :
Compute Options
Google Compute Engine (GCE)
More GCE
Lab: Creating a VM Instance
Lab: Editing a VM Instance
Lab: Creating a VM Instance Using The Command Line
Lab: Creating And Attaching A Persistent Disk
Google Container Engine - Kubernetes (GKE)
More GKE
Lab: Creating A Kubernetes Cluster And Deploying A Wordpress Container
App Engine
Contrasting App Engine, Compute Engine and Container Engine
Lab: Deploy And Run An App Engine App
21 questions

Storage :
Storage Options
Quick Take
Cloud Storage
Lab: Working With Cloud Storage Buckets
Lab: Bucket And Object Permissions
Lab: Life cycle Management On Buckets
Lab: Running A Program On a VM Instance And Storing Results on Cloud Storage
Transfer Service
Lab: Migrating Data Using The Transfer Service

Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS :
Cloud SQL
Lab: Creating A Cloud SQL Instance
Lab: Running Commands On Cloud SQL Instance
Lab: Bulk Loading Data Into Cloud SQL Tables
Cloud Spanner
More Cloud Spanner
Important! Delete unused GCP projects/instances
Lab: Working With Cloud Spanner

Hadoop Pre-reqs and Context :
Hadoop Pre-reqs and Context

BigTable ~ HBase = Columnar Store :
BigTable Intro
Columnar Store
Column Families
BigTable Performance
Important! Delete unused GCP projects/instances
Lab: BigTable demo

Datastore ~ Document Database :
Lab: Datastore demo

BigQuery ~ Hive ~ OLAP :
BigQuery Intro
BigQuery Advanced
Lab: Loading CSV Data Into Big Query
Lab: Running Queries On Big Query
Lab: Loading JSON Data With Nested Tables
Lab: Public Datasets In Big Query
Lab: Using Big Query Via The Command Line
Lab: Aggregations And Conditionals In Aggregations
Lab: Subqueries And Joins
Lab: Regular Expressions In Legacy SQL
Lab: Using The With Statement For SubQueries

Dataflow ~ Apache Beam :
Data Flow Intro
Apache Beam
Lab: Running A Python Data flow Program
Lab: Running A Java Data flow Program
Lab: Implementing Word Count In Dataflow Java
Lab: Executing The Word Count Dataflow
Lab: Executing MapReduce In Dataflow In Python
Lab: Executing MapReduce In Dataflow In Java
Lab: Dataflow With Big Query As Source And Side Inputs
Lab: Dataflow With Big Query As Source And Side Inputs 2

Dataproc ~ Managed Hadoop :
Data Proc
Lab: Creating And Managing A Dataproc Cluster
Lab: Creating A Firewall Rule To Access Dataproc
Lab: Running A PySpark Job On Dataproc
Lab: Running The PySpark REPL Shell And Pig Scripts On Dataproc
Lab: Submitting A Spark Jar To Dataproc
Lab: Working With Dataproc Using The GCloud CLI

Pub/Sub for Streaming :
Pub Sub
Lab: Working With Pubsub On The Command Line
Lab: Working With PubSub Using The Web Console
Lab: Setting Up A Pubsub Publisher Using The Python Library
Lab: Setting Up A Pubsub Subscriber Using The Python Library
Lab: Publishing Streaming Data Into Pubsub
Lab: Reading Streaming Data From PubSub And Writing To BigQuery
Lab: Executing A Pipeline To Read Streaming Data And Write To BigQuery
Lab: Pubsub Source BigQuery Sink

Datalab ~ Jupyter :
Data Lab
Lab: Creating And Working On A Datalab Instance
Lab: Importing And Exporting Data Using Datalab
Lab: Using The Charting API In Datalab

TensorFlow and Machine Learning :
Introducing Machine Learning
Representation Learning
NN Introduced
Introducing TF
Lab: Simple Math Operations
Computation Graph
Lab: Tensors
Linear Regression Intro
Placeholders and Variables
Lab: Placeholders
Lab: Variables
Lab: Linear Regression with Made-up Data
Image Processing
Images As Tensors
Lab: Reading and Working with Images
Lab: Image Transformations
Introducing MNIST
K-Nearest Neigbors as Unsupervised Learning
One-hot Notation and L1 Distance
Steps in the K-Nearest-Neighbors Implementation
Lab: K-Nearest-Neighbors
Learning Algorithm
Individual Neuron
Learning Regression
Learning XOR
XOR Trained

Regression in TensorFlow :
Lab: Access Data from Yahoo Finance
Non TensorFlow Regression
Lab: Linear Regression - Setting Up a Baseline
Gradient Descent
Lab: Linear Regression
Lab: Multiple Regression in TensorFlow
Logistic Regression Introduced
Linear Classification
Lab: Logistic Regression - Setting Up a Baseline
Lab: Logistic Regression
Lab: Linear Regression using Estimators
Lab: Logistic Regression using Estimators

Vision, Translate, NLP and Speech: Trained ML APIs :
Lab: Taxicab Prediction - Setting up the dataset
Lab: Taxicab Prediction - Training and Running the model
Lab: The Vision, Translate, NLP and Speech API
Lab: The Vision API for Label and Landmark Detection

Networking :
Virtual Private Clouds
VPC and Firewalls
XPC or Shared VPC
Types of Load Balancing
Proxy and Pass-through load balancing
Internal load balancing
11 questions

Ops and Security :
StackDriver Logging
Cloud Deployment Manager
Cloud Endpoints
Security and Service Accounts
OAuth and End-user accounts
Identity and Access Management
Data Protection
Operations and Security
5 questions
3 questions

Appendix: Hadoop Ecosystem :
Introducing the Hadoop Ecosystem
Hive vs. RDBMS
OLAP in Hive
Windowing Hive
More Pig
More Spark
Streams Intro
Window Types
Hadoop Ecosystem
6 questions

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