Section 1 : Introduction
Lecture 1 Welcome 00:02:12 Duration
Lecture 2 Preparing for the Google Cloud Professional Data Engineer Exam 00:03:27 Duration

Section 2 : Cloud Storage for Data Engineering
Lecture 1 Introduction to Object Storage 00:07:13 Duration
Lecture 2 Options for Loading Data 00:03:45 Duration
Lecture 3 Access Controls for Cloud Storage 00:02:15 Duration
Lecture 4 Lifecycle Policy Management 00:02:26 Duration
Lecture 5 Using Cloud Storage Console 00:05:16 Duration
Lecture 6 Exercise Cloud Storage 00:00:13 Duration
Lecture 7 Solution Cloud Storage 00:01:40 Duration

Section 3 : Relational Databases - Cloud SQL
Lecture 1 Introduction to Relational Databases 00:07:56 Duration
Lecture 2 When to use Cloud SQL 00:02:31 Duration
Lecture 3 Creating a Cloud SQL Database 00:05:00 Duration
Lecture 4 Monitoring Cloud SQL 00:02:13 Duration
Lecture 5 Exercise Create a Cloud SQL Database 00:00:31 Duration
Lecture 6 Solution Create a Cloud SQL Database 00:02:32 Duration

Section 4 : Relational Databases - Cloud Spanner
Lecture 1 When to use Cloud Spanner 00:01:36 Duration
Lecture 2 Creating a Cloud Spanner Database 00:03:57 Duration
Lecture 3 Cloud Spanner Performance Considerations 00:03:31 Duration

Section 5 : NoSQL Databases Cloud Firestore
Lecture 1 Introduction to Cloud Firestore & Document Databases 00:03:02 Duration
Lecture 2 Entities and Kinds 00:02:01 Duration
Lecture 3 Indexing in Cloud Firestore 00:01:48 Duration
Lecture 4 Creating Entities 00:03:56 Duration
Lecture 5 Querying Entities 00:02:49 Duration
Lecture 6 Creating Kinds and Namespaces 00:02:26 Duration
Lecture 7 Working with Transactions 00:01:59 Duration
Lecture 8 Exercise Create a Kind and Entities 00:00:28 Duration
Lecture 9 Solution Creating Kinds and Entities 00:01:22 Duration

Section 6 : NoSQL Databases Bigtable
Lecture 1 Introduction to Bigtable and Wide-Column Databases 00:04:33 Duration
Lecture 2 Creating a Bigtable Instance
Lecture 3 Designing Row-keys for Bigtable 00:05:33 Duration
Lecture 4 Query Patterns and Denormalization 00:04:01 Duration
Lecture 5 Designing for Time Series Data 00:04:49 Duration

Section 7 : Analytical Databases BigQuery Data Management
Lecture 1 Introduction to BigQuery and Analytical Databases 00:05:18 Duration
Lecture 2 BigQuery Scalar Datatypes 00:01:10 Duration
Lecture 3 BigQuery Nested and Repeated Fields 00:01:29 Duration
Lecture 4 Querying Scalars, Nested and Repeated Fields 00:04:31 Duration
Lecture 5 Exercise Querying BigQuery Public Datasets 00:00:28 Duration
Lecture 6 Solution Querying BigQuery Public Datasets 00:00:59 Duration
Lecture 7 Access Controls in BigQuery 00:01:15 Duration
Lecture 8 Partitioning Tables 00:04:43 Duration
Lecture 9 Clustering Partitioned Tables 00:01:06 Duration
Lecture 10 Loading Data into BigQuery 00:02:49 Duration

Section 8 : Migrating a Data Warehouse
Lecture 1 Assessing the Current State of a Data Warehouse 00:03:20 Duration
Lecture 2 Schema and Data Transfer 00:03:07 Duration
Lecture 3 Data Pipelines 00:01:58 Duration
Lecture 4 Reporting and Analysis 00:01:45 Duration
Lecture 5 Data Governance 00:02:20 Duration

Section 9 : Caching Data and Cloud Memorystore
Lecture 1 Using Caching to Improve Performance 00:04:28 Duration
Lecture 2 Cloud Memorystore Data Structures 00:02:02 Duration
Lecture 3 When to use Cloud Memorystore 00:04:01 Duration

Section 10 : Workflows and ETLELT
Lecture 1 Introduction to Cloud Composer 00:03:24 Duration
Lecture 2 Cloud Composer Architecture 00:03:18 Duration
Lecture 3 Introduction to Cloud Data Fusion 00:03:21 Duration

Section 11 : Cloud PubSub and Data Pipelines
Lecture 1 Introduction to Cloud PubSub 00:00:58 Duration
Lecture 2 Creating Topics and Subscriptions 00:02:51 Duration
Lecture 3 Creating and Reading Messages 00:02:05 Duration
Lecture 4 Exercise Create a Topic, Publish Messages, Read Messages 00:00:40 Duration
Lecture 5 Solution Create a Topic Publish Message 00:02:06 Duration

Section 12 : Cloud Dataflow and Data Pipelines
Lecture 1 Stream and Batch Processing with Cloud Dataflow 00:03:53 Duration
Lecture 2 Running a Job in Cloud Dataflow 00:04:20 Duration
Lecture 3 Analyzing a Failed Job in Cloud Dataflow 00:03:04 Duration
Lecture 4 Monitoring Cloud Dataflow 00:02:55 Duration
Lecture 5 Troubleshooting a Cloud Dataflow Pipeline 00:02:09 Duration

Section 13 : Cloud Dataproc and Data Pipelines
Lecture 1 Introduction to Cloud Dataproc 00:03:30 Duration
Lecture 2 Creating a Cloud Dataproc Cluster 00:05:52 Duration
Lecture 3 Monitoring a Cloud Dataproc Cluster 00:01:39 Duration
Lecture 4 Using Cloud Storage with Cloud Dataproc

Section 14 : Special Considerations in Distributed Systems
Lecture 1 Hybrid and multi-cloud computing 00:03:59 Duration
Lecture 2 Asychronous Messaging 00:04:54 Duration
Lecture 3 Stream Processing 00:07:45 Duration
Lecture 4 Data Consistency Models 00:03:14 Duration

Section 15 : Monitoring and Logging
Lecture 1 Monitoring and Alerting with Cloud Monitoring 00:04:24 Duration
Lecture 2 Logging with Cloud Logging 00:03:23 Duration
Lecture 3 Creating an Alert 00:02:54 Duration
Lecture 4 Install the Monitoring Agent on a Virtual Machine 00:04:08 Duration

Section 16 : Security and Compliance
Lecture 1 Introduction to Identity Access Management
Lecture 2 Resource Hierarchy 00:01:44 Duration
Lecture 3 Predefined Roles
Lecture 4 Custom Roles 00:03:57 Duration
Lecture 5 Primitive Roles 00:01:28 Duration
Lecture 6 IAM Best Practices 00:02:11 Duration
Lecture 7 Ensuring Privacy with Data Loss Prevention API 00:04:04 Duration
Lecture 8 Legal Compliance 00:02:54 Duration
Lecture 9 Encryption At Rest and In Motion 00:06:16 Duration
Lecture 10 Key Management 00:02:58 Duration
Lecture 11 Exercise Grant roles to users 00:00:20 Duration
Lecture 12 Solution Grant roles to users 00:00:49 Duration

Section 17 : Introduction to Machine Learning
Lecture 1 3 Categories of Machine Learning Problems 00:03:16 Duration
Lecture 2 2 Approaches to Building ML Models 00:01:05 Duration
Lecture 3 Symbolic Machine Learning 00:05:44 Duration
Lecture 4 Neural Networks and Deep Learning 00:04:20 Duration

Section 18 : Building ML Models
Lecture 1 Features and Labels 00:02:30 Duration
Lecture 2 Feature Engineering 00:05:18 Duration
Lecture 3 Model Building 00:03:49 Duration
Lecture 4 Model Evaluation 00:05:18 Duration
Lecture 5 Gradient Descent and Backpropagation 00:07:23 Duration
Lecture 6 Model Troubleshooting 00:05:11 Duration
Lecture 7 Building Models in GCP
Lecture 8 Using Pre-built ML Models 00:02:39 Duration

Section 19 : Deploying and Monitoring ML Models
Lecture 1 Options for Deploying ML Models 00:02:48 Duration
Lecture 2 Using GPUs and TPUs 00:01:53 Duration
Lecture 3 Monitoring ML Models 00:03:09 Duration
Lecture 4 Bias and Unfairness in ML Models 00:02:09 Duration

Section 20 : Analytical Databases BigQuery ML
Lecture 1 Introduction to Machine Learning in BigQuery 00:03:06 Duration
Lecture 2 Creating a Regression Model in BigQuery 00:02:31 Duration
Lecture 3 Evaluating a Regression Model in BigQuery 00:01:36 Duration
Lecture 4 Using Model for Predictions in BigQuery 00:01:36 Duration
Lecture 5 Exercise Creating a Model in BigQuery 00:00:18 Duration
Lecture 6 Solution Creating an ML Model in BigQuery 00:00:26 Duration

Section 21 : Conclusion
Lecture 1 Conclusion and Next Steps 00:02:55 Duration