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Professional Data Engineer: Professional Data Engineer on Google Cloud Platform Certification Video Training Course

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  • 86 Students Enrolled
  • 201 Lectures
  • 3 Hours
  • 4.4 Rating
$38.49
$34.99

Curriculum For This Course

  • You, This Course and Us

    Video Name Time
    1. You, This Course and Us 02:01

  • Introduction

    Video Name Time
    1. Theory, Practice and Tests 10:26
    2. Lab: Setting Up A GCP Account 07:00
    3. Lab: Using The Cloud Shell 06:01

  • Compute

    Video Name Time
    1. Compute Options 09:16
    2. Google Compute Engine (GCE) 07:38
    3. Lab: Creating a VM Instance 05:59
    4. More GCE 08:12
    5. Lab: Editing a VM Instance 04:45
    6. Lab: Creating a VM Instance Using The Command Line 04:43
    7. Lab: Creating And Attaching A Persistent Disk 04:00
    8. Google Container Engine - Kubernetes (GKE) 10:33
    9. More GKE 09:54
    10. Lab: Creating A Kubernetes Cluster And Deploying A Wordpress Container 06:55
    11. App Engine 06:48
    12. Contrasting App Engine, Compute Engine and Container Engine 06:03
    13. Lab: Deploy And Run An App Engine App 07:29

  • Storage

    Video Name Time
    1. Storage Options 09:48
    2. Quick Take 13:41
    3. Cloud Storage 10:37
    4. Lab: Working With Cloud Storage Buckets 05:25
    5. Lab: Bucket And Object Permissions 03:52
    6. Lab: Life cycle Management On Buckets 03:12
    7. Lab: Running A Program On a VM Instance And Storing Results on Cloud Storage 07:09
    8. Transfer Service 05:07
    9. Lab: Migrating Data Using The Transfer Service 05:32
    10. Lab: Cloud Storage ACLs and API access with Service Account 07:50
    11. Lab: Cloud Storage Customer-Supplied Encryption Keys and Life-Cycle Management 09:28
    12. Lab: Cloud Storage Versioning, Directory Sync 08:42

  • Cloud SQL, Cloud Spanner ~ OLTP ~ RDBMS

    Video Name Time
    1. Cloud SQL 07:40
    2. Lab: Creating A Cloud SQL Instance 07:55
    3. Lab: Running Commands On Cloud SQL Instance 06:31
    4. Lab: Bulk Loading Data Into Cloud SQL Tables 09:09
    5. Cloud Spanner 07:25
    6. More Cloud Spanner 09:18
    7. Lab: Working With Cloud Spanner 06:49

  • BigTable ~ HBase = Columnar Store

    Video Name Time
    1. BigTable Intro 07:57
    2. Columnar Store 08:12
    3. Denormalised 09:02
    4. Column Families 08:10
    5. BigTable Performance 13:19
    6. Lab: BigTable demo 07:39

  • Datastore ~ Document Database

    Video Name Time
    1. Datastore 14:10
    2. Lab: Datastore demo 06:42

  • BigQuery ~ Hive ~ OLAP

    Video Name Time
    1. BigQuery Intro 11:03
    2. BigQuery Advanced 09:59
    3. Lab: Loading CSV Data Into Big Query 09:04
    4. Lab: Running Queries On Big Query 05:26
    5. Lab: Loading JSON Data With Nested Tables 07:28
    6. Lab: Public Datasets In Big Query 08:16
    7. Lab: Using Big Query Via The Command Line 07:45
    8. Lab: Aggregations And Conditionals In Aggregations 09:51
    9. Lab: Subqueries And Joins 05:44
    10. Lab: Regular Expressions In Legacy SQL 05:36
    11. Lab: Using The With Statement For SubQueries 10:45

  • Dataflow ~ Apache Beam

    Video Name Time
    1. Data Flow Intro 11:04
    2. Apache Beam 03:42
    3. Lab: Running A Python Data flow Program 12:56
    4. Lab: Running A Java Data flow Program 13:42
    5. Lab: Implementing Word Count In Dataflow Java 11:17
    6. Lab: Executing The Word Count Dataflow 04:37
    7. Lab: Executing MapReduce In Dataflow In Python 09:50
    8. Lab: Executing MapReduce In Dataflow In Java 06:08
    9. Lab: Dataflow With Big Query As Source And Side Inputs 15:50
    10. Lab: Dataflow With Big Query As Source And Side Inputs 2 06:28

  • Dataproc ~ Managed Hadoop

    Video Name Time
    1. Data Proc 08:28
    2. Lab: Creating And Managing A Dataproc Cluster 08:11
    3. Lab: Creating A Firewall Rule To Access Dataproc 08:25
    4. Lab: Running A PySpark Job On Dataproc 07:39
    5. Lab: Running The PySpark REPL Shell And Pig Scripts On Dataproc 08:44
    6. Lab: Submitting A Spark Jar To Dataproc 02:10
    7. Lab: Working With Dataproc Using The GCloud CLI 08:19

  • Pub/Sub for Streaming

    Video Name Time
    1. Pub Sub 08:23
    2. Lab: Working With Pubsub On The Command Line 05:35
    3. Lab: Working With PubSub Using The Web Console 04:40
    4. Lab: Setting Up A Pubsub Publisher Using The Python Library 05:52
    5. Lab: Setting Up A Pubsub Subscriber Using The Python Library 04:08
    6. Lab: Publishing Streaming Data Into Pubsub 08:18
    7. Lab: Reading Streaming Data From PubSub And Writing To BigQuery 10:14
    8. Lab: Executing A Pipeline To Read Streaming Data And Write To BigQuery 05:54
    9. Lab: Pubsub Source BigQuery Sink 10:20

  • Datalab ~ Jupyter

    Video Name Time
    1. Data Lab 03:00
    2. Lab: Creating And Working On A Datalab Instance 04:01
    3. Lab: Importing And Exporting Data Using Datalab 12:14
    4. Lab: Using The Charting API In Datalab 06:43

  • TensorFlow and Machine Learning

    Video Name Time
    1. Introducing Machine Learning 08:04
    2. Representation Learning 10:27
    3. NN Introduced 07:35
    4. Introducing TF 07:16
    5. Lab: Simple Math Operations 08:46
    6. Computation Graph 10:17
    7. Tensors 09:02
    8. Lab: Tensors 05:03
    9. Linear Regression Intro 09:57
    10. Placeholders and Variables 08:44
    11. Lab: Placeholders 06:36
    12. Lab: Variables 07:49
    13. Lab: Linear Regression with Made-up Data 04:52
    14. Image Processing 08:05
    15. Images As Tensors 08:16
    16. Lab: Reading and Working with Images 08:06
    17. Lab: Image Transformations 06:37
    18. Introducing MNIST 04:13
    19. K-Nearest Neigbors 07:42
    20. One-hot Notation and L1 Distance 07:31
    21. Steps in the K-Nearest-Neighbors Implementation 09:32
    22. Lab: K-Nearest-Neighbors 14:14
    23. Learning Algorithm 10:58
    24. Individual Neuron 09:52
    25. Learning Regression 07:51
    26. Learning XOR 10:27
    27. XOR Trained 11:11

  • Regression in TensorFlow

    Video Name Time
    1. Lab: Access Data from Yahoo Finance 02:49
    2. Non TensorFlow Regression 05:53
    3. Lab: Linear Regression - Setting Up a Baseline 11:19
    4. Gradient Descent 09:56
    5. Lab: Linear Regression 14:42
    6. Lab: Multiple Regression in TensorFlow 09:15
    7. Logistic Regression Introduced 10:16
    8. Linear Classification 05:25
    9. Lab: Logistic Regression - Setting Up a Baseline 07:33
    10. Logit 08:33
    11. Softmax 11:55
    12. Argmax 12:13
    13. Lab: Logistic Regression 16:56
    14. Estimators 04:10
    15. Lab: Linear Regression using Estimators 07:49
    16. Lab: Logistic Regression using Estimators 04:54

  • Vision, Translate, NLP and Speech: Trained ML APIs

    Video Name Time
    1. Lab: Taxicab Prediction - Setting up the dataset 14:38
    2. Lab: Taxicab Prediction - Training and Running the model 11:22
    3. Lab: The Vision, Translate, NLP and Speech API 10:54
    4. Lab: The Vision API for Label and Landmark Detection 07:00

  • Virtual Machines and Images

    Video Name Time
    1. Live Migration 10:17
    2. Machine Types and Billing 09:21
    3. Sustained Use and Committed Use Discounts 07:03
    4. Rightsizing Recommendations 02:22
    5. RAM Disk 02:07
    6. Images 07:45
    7. Startup Scripts And Baked Images 07:31

  • VPCs and Interconnecting Networks

    Video Name Time
    1. VPCs And Subnets 11:14
    2. Global VPCs, Regional Subnets 11:19
    3. IP Addresses 11:39
    4. Lab: Working with Static IP Addresses 05:46
    5. Routes 07:36
    6. Firewall Rules 15:33
    7. Lab: Working with Firewalls 07:05
    8. Lab: Working with Auto Mode and Custom Mode Networks 19:32
    9. Lab: Bastion Host 07:10
    10. Cloud VPN 07:27
    11. Lab: Working with Cloud VPN 11:11
    12. Cloud Router 10:31
    13. Lab: Using Cloud Routers for Dynamic Routing 14:07
    14. Dedicated Interconnect Direct and Carrier Peering 08:10
    15. Shared VPCs 10:11
    16. Lab: Shared VPCs 06:17
    17. VPC Network Peering 10:10
    18. Lab: VPC Peering 07:17
    19. Cloud DNS And Legacy Networks 05:19

  • Managed Instance Groups and Load Balancing

    Video Name Time
    1. Managed and Unmanaged Instance Groups 10:53
    2. Types of Load Balancing 05:46
    3. Overview of HTTP(S) Load Balancing 09:20
    4. Forwarding Rules Target Proxy and Url Maps 08:31
    5. Backend Service and Backends 09:28
    6. Load Distribution and Firewall Rules 04:28
    7. Lab: HTTP(S) Load Balancing 11:21
    8. Lab: Content Based Load Balancing 07:06
    9. SSL Proxy and TCP Proxy Load Balancing 05:06
    10. Lab: SSL Proxy Load Balancing 07:49
    11. Network Load Balancing 05:08
    12. Internal Load Balancing 07:16
    13. Autoscalers 11:52
    14. Lab: Autoscaling with Managed Instance Groups 12:22

  • Ops and Security

    Video Name Time
    1. StackDriver 12:08
    2. StackDriver Logging 07:39
    3. Lab: Stackdriver Resource Monitoring 08:12
    4. Lab: Stackdriver Error Reporting and Debugging 05:52
    5. Cloud Deployment Manager 06:05
    6. Lab: Using Deployment Manager 05:10
    7. Lab: Deployment Manager and Stackdriver 08:27
    8. Cloud Endpoints 03:48
    9. Cloud IAM: User accounts, Service accounts, API Credentials 08:53
    10. Cloud IAM: Roles, Identity-Aware Proxy, Best Practices 09:31
    11. Lab: Cloud IAM 11:57
    12. Data Protection 12:02

  • Appendix: Hadoop Ecosystem

    Video Name Time
    1. Introducing the Hadoop Ecosystem 01:34
    2. Hadoop 09:43
    3. HDFS 10:55
    4. MapReduce 10:34
    5. Yarn 05:29
    6. Hive 07:19
    7. Hive vs. RDBMS 07:10
    8. HQL vs. SQL 07:36
    9. OLAP in Hive 07:34
    10. Windowing Hive 08:22
    11. Pig 08:04
    12. More Pig 06:38
    13. Spark 08:54
    14. More Spark 11:45
    15. Streams Intro 07:44
    16. Microbatches 05:40
    17. Window Types 05:46

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