Professional Data Engineer on Google Cloud Platform Video Course

Professional Data Engineer: Professional Data Engineer on Google Cloud Platform

Your Google Professional Data Engineer exam is just around the corner, right? So, it's high time to find an effective preparation tool! Our training course is what you really need! This is a series of videos led by the experienced IT instructors who will provide you with a detailed overview of the Professional Data Engineer certification test. Ace your Google Professional Data Engineer at the first attempt and obtain the Professional Data Engineer on Google Cloud Platform credential with ease.

# of Students
115
# of Lectures
201
Course Length
3 h
Course Rating
4.5
Price $32.99
Today $29.99

Curriculum for Professional Data Engineer Video Course

You, This Course and Us

  Video Name Time
  1. You, This Course and Us 02:01
  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
  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
  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
  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
  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
  Video Name Time
  1. Datastore 14:10
  2. Lab: Datastore demo 06:42
  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
  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
  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
  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
  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
  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
  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
  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
  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
  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
  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
  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
  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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