Professional Data Engineer: Professional Data Engineer on Google Cloud Platform

Get ready for your exam by enrolling in our comprehensive training course. This course includes a full set of instructional videos designed to equip you with in-depth knowledge essential for passing the certification exam with flying colors.

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You, This Course and Us

1. You, This Course and Us
2m 1s

Introduction

1. Theory, Practice and Tests
10m 26s
2. Lab: Setting Up A GCP Account
7m
3. Lab: Using The Cloud Shell
6m 1s

Compute

1. Compute Options
9m 16s
2. Google Compute Engine (GCE)
7m 38s
3. Lab: Creating a VM Instance
5m 59s
4. More GCE
8m 12s
5. Lab: Editing a VM Instance
4m 45s
6. Lab: Creating a VM Instance Using The Command Line
4m 43s
7. Lab: Creating And Attaching A Persistent Disk
4m
8. Google Container Engine - Kubernetes (GKE)
10m 33s
9. More GKE
9m 54s
10. Lab: Creating A Kubernetes Cluster And Deploying A Wordpress Container
6m 55s
11. App Engine
6m 48s
12. Contrasting App Engine, Compute Engine and Container Engine
6m 3s
13. Lab: Deploy And Run An App Engine App
7m 29s

Storage

1. Storage Options
9m 48s
2. Quick Take
13m 41s
3. Cloud Storage
10m 37s
4. Lab: Working With Cloud Storage Buckets
5m 25s
5. Lab: Bucket And Object Permissions
3m 52s
6. Lab: Life cycle Management On Buckets
3m 12s
7. Lab: Running A Program On a VM Instance And Storing Results on Cloud Storage
7m 9s
8. Transfer Service
5m 7s
9. Lab: Migrating Data Using The Transfer Service
5m 32s
10. Lab: Cloud Storage ACLs and API access with Service Account
7m 50s
11. Lab: Cloud Storage Customer-Supplied Encryption Keys and Life-Cycle Management
9m 28s
12. Lab: Cloud Storage Versioning, Directory Sync
8m 42s

Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS

1. Cloud SQL
7m 40s
2. Lab: Creating A Cloud SQL Instance
7m 55s
3. Lab: Running Commands On Cloud SQL Instance
6m 31s
4. Lab: Bulk Loading Data Into Cloud SQL Tables
9m 9s
5. Cloud Spanner
7m 25s
6. More Cloud Spanner
9m 18s
7. Lab: Working With Cloud Spanner
6m 49s

BigTable ~ HBase = Columnar Store

1. BigTable Intro
7m 57s
2. Columnar Store
8m 12s
3. Denormalised
9m 2s
4. Column Families
8m 10s
5. BigTable Performance
13m 19s
6. Lab: BigTable demo
7m 39s

Datastore ~ Document Database

1. Datastore
14m 10s
2. Lab: Datastore demo
6m 42s

BigQuery ~ Hive ~ OLAP

1. BigQuery Intro
11m 3s
2. BigQuery Advanced
9m 59s
3. Lab: Loading CSV Data Into Big Query
9m 4s
4. Lab: Running Queries On Big Query
5m 26s
5. Lab: Loading JSON Data With Nested Tables
7m 28s
6. Lab: Public Datasets In Big Query
8m 16s
7. Lab: Using Big Query Via The Command Line
7m 45s
8. Lab: Aggregations And Conditionals In Aggregations
9m 51s
9. Lab: Subqueries And Joins
5m 44s
10. Lab: Regular Expressions In Legacy SQL
5m 36s
11. Lab: Using The With Statement For SubQueries
10m 45s

Dataflow ~ Apache Beam

1. Data Flow Intro
11m 4s
2. Apache Beam
3m 42s
3. Lab: Running A Python Data flow Program
12m 56s
4. Lab: Running A Java Data flow Program
13m 42s
5. Lab: Implementing Word Count In Dataflow Java
11m 17s
6. Lab: Executing The Word Count Dataflow
4m 37s
7. Lab: Executing MapReduce In Dataflow In Python
9m 50s
8. Lab: Executing MapReduce In Dataflow In Java
6m 8s
9. Lab: Dataflow With Big Query As Source And Side Inputs
15m 50s
10. Lab: Dataflow With Big Query As Source And Side Inputs 2
6m 28s

Dataproc ~ Managed Hadoop

1. Data Proc
8m 28s
2. Lab: Creating And Managing A Dataproc Cluster
8m 11s
3. Lab: Creating A Firewall Rule To Access Dataproc
8m 25s
4. Lab: Running A PySpark Job On Dataproc
7m 39s
5. Lab: Running The PySpark REPL Shell And Pig Scripts On Dataproc
8m 44s
6. Lab: Submitting A Spark Jar To Dataproc
2m 10s
7. Lab: Working With Dataproc Using The GCloud CLI
8m 19s

Pub/Sub for Streaming

1. Pub Sub
8m 23s
2. Lab: Working With Pubsub On The Command Line
5m 35s
3. Lab: Working With PubSub Using The Web Console
4m 40s
4. Lab: Setting Up A Pubsub Publisher Using The Python Library
5m 52s
5. Lab: Setting Up A Pubsub Subscriber Using The Python Library
4m 8s
6. Lab: Publishing Streaming Data Into Pubsub
8m 18s
7. Lab: Reading Streaming Data From PubSub And Writing To BigQuery
10m 14s
8. Lab: Executing A Pipeline To Read Streaming Data And Write To BigQuery
5m 54s
9. Lab: Pubsub Source BigQuery Sink
10m 20s

Datalab ~ Jupyter

1. Data Lab
3m
2. Lab: Creating And Working On A Datalab Instance
4m 1s
3. Lab: Importing And Exporting Data Using Datalab
12m 14s
4. Lab: Using The Charting API In Datalab
6m 43s

TensorFlow and Machine Learning

1. Introducing Machine Learning
8m 4s
2. Representation Learning
10m 27s
3. NN Introduced
7m 35s
4. Introducing TF
7m 16s
5. Lab: Simple Math Operations
8m 46s
6. Computation Graph
10m 17s
7. Tensors
9m 2s
8. Lab: Tensors
5m 3s
9. Linear Regression Intro
9m 57s
10. Placeholders and Variables
8m 44s
11. Lab: Placeholders
6m 36s
12. Lab: Variables
7m 49s
13. Lab: Linear Regression with Made-up Data
4m 52s
14. Image Processing
8m 5s
15. Images As Tensors
8m 16s
16. Lab: Reading and Working with Images
8m 6s
17. Lab: Image Transformations
6m 37s
18. Introducing MNIST
4m 13s
19. K-Nearest Neigbors
7m 42s
20. One-hot Notation and L1 Distance
7m 31s
21. Steps in the K-Nearest-Neighbors Implementation
9m 32s
22. Lab: K-Nearest-Neighbors
14m 14s
23. Learning Algorithm
10m 58s
24. Individual Neuron
9m 52s
25. Learning Regression
7m 51s
26. Learning XOR
10m 27s
27. XOR Trained
11m 11s

Regression in TensorFlow

1. Lab: Access Data from Yahoo Finance
2m 49s
2. Non TensorFlow Regression
5m 53s
3. Lab: Linear Regression - Setting Up a Baseline
11m 19s
4. Gradient Descent
9m 56s
5. Lab: Linear Regression
14m 42s
6. Lab: Multiple Regression in TensorFlow
9m 15s
7. Logistic Regression Introduced
10m 16s
8. Linear Classification
5m 25s
9. Lab: Logistic Regression - Setting Up a Baseline
7m 33s
10. Logit
8m 33s
11. Softmax
11m 55s
12. Argmax
12m 13s
13. Lab: Logistic Regression
16m 56s
14. Estimators
4m 10s
15. Lab: Linear Regression using Estimators
7m 49s
16. Lab: Logistic Regression using Estimators
4m 54s

Vision, Translate, NLP and Speech: Trained ML APIs

1. Lab: Taxicab Prediction - Setting up the dataset
14m 38s
2. Lab: Taxicab Prediction - Training and Running the model
11m 22s
3. Lab: The Vision, Translate, NLP and Speech API
10m 54s
4. Lab: The Vision API for Label and Landmark Detection
7m

Virtual Machines and Images

1. Live Migration
10m 17s
2. Machine Types and Billing
9m 21s
3. Sustained Use and Committed Use Discounts
7m 3s
4. Rightsizing Recommendations
2m 22s
5. RAM Disk
2m 7s
6. Images
7m 45s
7. Startup Scripts And Baked Images
7m 31s

VPCs and Interconnecting Networks

1. VPCs And Subnets
11m 14s
2. Global VPCs, Regional Subnets
11m 19s
3. IP Addresses
11m 39s
4. Lab: Working with Static IP Addresses
5m 46s
5. Routes
7m 36s
6. Firewall Rules
15m 33s
7. Lab: Working with Firewalls
7m 5s
8. Lab: Working with Auto Mode and Custom Mode Networks
19m 32s
9. Lab: Bastion Host
7m 10s
10. Cloud VPN
7m 27s
11. Lab: Working with Cloud VPN
11m 11s
12. Cloud Router
10m 31s
13. Lab: Using Cloud Routers for Dynamic Routing
14m 7s
14. Dedicated Interconnect Direct and Carrier Peering
8m 10s
15. Shared VPCs
10m 11s
16. Lab: Shared VPCs
6m 17s
17. VPC Network Peering
10m 10s
18. Lab: VPC Peering
7m 17s
19. Cloud DNS And Legacy Networks
5m 19s

Managed Instance Groups and Load Balancing

1. Managed and Unmanaged Instance Groups
10m 53s
2. Types of Load Balancing
5m 46s
3. Overview of HTTP(S) Load Balancing
9m 20s
4. Forwarding Rules Target Proxy and Url Maps
8m 31s
5. Backend Service and Backends
9m 28s
6. Load Distribution and Firewall Rules
4m 28s
7. Lab: HTTP(S) Load Balancing
11m 21s
8. Lab: Content Based Load Balancing
7m 6s
9. SSL Proxy and TCP Proxy Load Balancing
5m 6s
10. Lab: SSL Proxy Load Balancing
7m 49s
11. Network Load Balancing
5m 8s
12. Internal Load Balancing
7m 16s
13. Autoscalers
11m 52s
14. Lab: Autoscaling with Managed Instance Groups
12m 22s

Ops and Security

1. StackDriver
12m 8s
2. StackDriver Logging
7m 39s
3. Lab: Stackdriver Resource Monitoring
8m 12s
4. Lab: Stackdriver Error Reporting and Debugging
5m 52s
5. Cloud Deployment Manager
6m 5s
6. Lab: Using Deployment Manager
5m 10s
7. Lab: Deployment Manager and Stackdriver
8m 27s
8. Cloud Endpoints
3m 48s
9. Cloud IAM: User accounts, Service accounts, API Credentials
8m 53s
10. Cloud IAM: Roles, Identity-Aware Proxy, Best Practices
9m 31s
11. Lab: Cloud IAM
11m 57s
12. Data Protection
12m 2s

Appendix: Hadoop Ecosystem

1. Introducing the Hadoop Ecosystem
1m 34s
2. Hadoop
9m 43s
3. HDFS
10m 55s
4. MapReduce
10m 34s
5. Yarn
5m 29s
6. Hive
7m 19s
7. Hive vs
7m 10s
8. HQL vs
7m 36s
9. OLAP in Hive
7m 34s
10. Windowing Hive
8m 22s
11. Pig
8m 4s
12. More Pig
6m 38s
13. Spark
8m 54s
14. More Spark
11m 45s
15. Streams Intro
7m 44s
16. Microbatches
5m 40s
17. Window Types
5m 46s