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Google Cloud Platform: Data Engineering Track
You, This Course and Us
You, This Course and Us
Course Materials
Introduction
Theory, Practice and Tests
Lab: Setting Up A GCP Account
Why Cloud?
Hadoop and Distributed Computing
On-premise, Colocation or Cloud?
Introducing the Google Cloud Platform
Lab: Using The Cloud Shell
Important! Delete unused GCP projects/instances
Quiz 1 GCP Introduction
Storage
About this section
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
Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS
About this section
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
Lab: Working With Cloud Spanner
Important! Delete unused GCP projects/instances
Hadoop Pre-reqs and Context
Hadoop Pre-reqs and Context
BigTable ~ HBase = Columnar Store
About this section
BigTable Intro
Columnar Store
Denormalised
Column Families
BigTable Performance
Lab: BigTable demo
Important! Delete unused GCP projects/instances
Datastore ~ Document Database
About this section
Datastore
Lab: Datastore demo
Quiz 3 Datastore
BigQuery ~ Hive ~ OLAP
About this section
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
About this section
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
About this section
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
About this section
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
About this section
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
About this section
Introducing Machine Learning
Representation Learning
NN Introduced
Introducing TF
Lab: Simple Math Operations
Computation Graph
Tensors
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
About this section
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
Logit
Softmax
Argmax
Lab: Logistic Regression
Estimators
Lab: Linear Regression using Estimators
Lab: Logistic Regression using Estimators
Vision, Translate, NLP and Speech: Trained ML APIs
About this section
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
Appendix: Hadoop Ecosystem
Introducing the Hadoop Ecosystem
Hadoop
HDFS
MapReduce
Yarn
Hive
Hive v RDBMS
HQL vs. SQL
OLAP in Hive
Windowing Hive
Pig
More Pig
Spark
More Spark
Streams Intro
Microbatches
Window Types
Quiz 6 Hadoop Ecosystem
Steps in the K-Nearest-Neighbors Implementation
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