Become An Aws Certified Data Engineer
Become An Aws Certified Data Engineer
Published 1/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 10.67 GB | Duration: 18h 21m
Learn how to become an AWS Certified Data Engineer -Associate with hands-on learning.
What you'll learn
Understanding AWS data storage options: Amazon S3, RDS, DynamoDB
Ingest and transform data, and orchestrate data pipelines while applying programming concepts.
Choose an optimal data store, design data models, catalog data schemas, and manage data lifecycles.
Operationalize, maintain, and monitor data pipelines. Analyze data and ensure data quality
Implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues
Working with AWS Data Pipeline for data movement and processing
Key concepts of AWS Glue for ETL processes
Querying data in S3 using AWS Athena
Requirements
An understanding of the AWS services for encryption, governance, protection, and logging of all data that is part of data pipelines
The ability to compare AWS services to understand the cost, performance, and functional differences between services
AWS Foundational knowledge of services
General concepts for networking, storage, and compute
Description
The AWS Certified Data Engineer - Associate (DEA-C01) exam validates a candidate's ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices.[v2024: This course is based on the current beta exam and the official exam guide. We'll keep it updated as final exams are released by AWS. Happy learning]You should have the equivalent of 2–3 years of experience in data engineering. The target candidate should understand the effects of volume, variety, and velocity on data ingestion, transformation, modeling, security, governance, privacy, schema design, and optimal data store design. Additionally, the target candidate should have at least 1–2 years of hands-on experience with AWS services.Why should you get AWS Certified?Getting AWS Certified can help you propel your career, whether you're looking to find a new role, showcase your skills to take on a new project, or become your team's go-to expert. And because AWS Certification exams are created by experts in the relevant role or technical area, preparing for one of these exams helps you build the required skills identified by skilled practitioners in the field.See what our students say "It is such a comprehensive course that I don't need to take any other course but this one to learn all important concepts and hand-on application with this AWS Certified Data Engineer - Associate course, and I would without a doubt recommend it to everyone." - Martha Jones"This is such an awesome course. Clear instruction, and I loved every bit of it – Wonderful learning experience!" Carlos Nelson.Join thousands of other students and share valuable experience.This course also comes with:Lifetime access to all future updatesA responsive instructor in the Q&A SectionUdemy Certificate of Completion Ready for DownloadA 30 Day "No Questions Asked" Money Back Guarantee!FREE AWS Certified Data Engineer- Associate quizzes and sample exam within this course.FREE E-Book on AWS Cost OptimizationWhy take this course?As 8x AWS, Microsoft, and Cisco Certified, a senior Enterprise Architect & Project Manager managing and deploying enterprise level IT projects, my experience with AWS has been phenomenally great! I am excited to share my knowledge and transfer skills to my students. Enroll now in AWS Certified Data Engineer - Associate (DEA-C01) course today and revolutionize your learning. Stay at the cutting edge of certification and AWS architectures- and enjoy bigger, brighter opportunities.See you in class.Syed Team ClayDesk
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Course Structure and Agenda
Lecture 3 Important Note
Lecture 4 Day-to-Day Activities of an AWS Data Engineer
Lecture 5 Note Taking
Lecture 6 The Value of AWS Certified Data Engineer
Lecture 7 What is Data Analytics and Data Analysis Solutions
Lecture 8 How to Create S3 Bucket with Amazon Q and New AWS Management Console
Lecture 9 Challenges of Data Analytics
Section 2: Data Ingestion and Transformation (34% of scored content)
Lecture 10 Throughput VS Latency
Lecture 11 Replayability, Stateful Vs Stateless Transactions
Lecture 12 ETL Process
Lecture 13 AWS Step Functions Use Cases Architectures
Lecture 14 Exercise: AWS Step Functions
Lecture 15 AWS Step Functions Workshop
Lecture 16 AWS Athena
Lecture 17 What is Kubernetes?
Lecture 18 How to Create Kubernetes Cluster?
Lecture 19 Cloud VS Distributed Computing
Lecture 20 Common Data Transformation Issues and Debugging
Lecture 21 Understanding DevOps
Lecture 22 Continuous Integration Continuous Delivery
Lecture 23 CICD Difference
Lecture 24 What is Fan-in Fan-out in Stream Data Distribution
Lecture 25 Understanding Even Driven Architecture
Lecture 26 How to configure AWS services for data pipelines?
Section 3: Cloud Data Migration
Lecture 27 Cloud Migration Benefits
Lecture 28 Cloud Migration Strategies
Lecture 29 Cloud Migration Process
Lecture 30 AWS Migration Hub
Lecture 31 Discovering your network infrastructure
Lecture 32 Migrating your network infrastructure
Lecture 33 Amazon EC2 recommendations
Lecture 34 Migration acceleration program
Lecture 35 AWS managed services
Lecture 36 AWS Cloud data migration services
Lecture 37 Online and offline data migration
Lecture 38 Server migration service
Lecture 39 How database migration service works
Lecture 40 Database migration use cases
Lecture 41 AWS Schema conversion tool
Lecture 42 Sample database migration to AWS
Lecture 43 Database migration best practices
Section 4: Domain 2: Data Store Management (26% of scored content)
Lecture 44 Data Volume
Lecture 45 Types of Data
Lecture 46 AWS S3 Storage Explained
Lecture 47 How to Create Amazon S3 Bucket
Lecture 48 Create S3 Bucket and Cross Region Replication
Lecture 49 Introduction to Data Lakes Architecture
Lecture 50 AWS Data Lake In-Depth
Lecture 51 AWS Glue - AWS Athena
Lecture 52 Data Storage Methods
Lecture 53 Data Warehouses
Lecture 54 Amazon RDS
Lecture 55 Amazon DynamoDB
Lecture 56 AWS DynamoDB Hands-on Lab
Lecture 57 Amazon SageMaker
Section 5: AWS Sage Maker and Machine Learning
Lecture 58 The AWS Machine Learning Service
Lecture 59 First steps in building a ML Model
Lecture 60 Understanding AWS Datasources
Lecture 61 ML Training Models
Lecture 62 Importance of Feature Transformation
Lecture 63 Evaluating Models
Lecture 64 Preparing data for Machine Learning
Lecture 65 Creating a datasource and model in AWS
Lecture 66 Serverless ML Inference with AWS Lambda
Lecture 67 What is SageMaker Revisited
Lecture 68 Setting up AWS to use SageMaker
Lecture 69 Machine Learning in SageMaker
Lecture 70 Intro to Linear Learner
Lecture 71 Preparing data for Linear Learner algorithm
Lecture 72 Training data using Linear Learner
Lecture 73 Creating a hyperparameter tuning job
Section 6: Domain 3: Data Operations and Support (22% of scored content) Velocity Data
Lecture 74 Batch Data Processing
Lecture 75 Batch Processing Architecture
Lecture 76 Velocity of Data Challenges
Lecture 77 Stream Data Processing
Section 7: AWS EC2 Deep Dive
Lecture 78 EC2 Basic Infrastructure
Lecture 79 Viewing your service limits
Lecture 80 Instance lifecycle
Lecture 81 Instance Types
Lecture 82 Launching your first instance
Lecture 83 Working with launch templates
Lecture 84 Launching an instance from an existing instance
Lecture 85 Instance states
Lecture 86 Connecting to a Windows Instance
Lecture 87 Connecting to a Linux Instance
Lecture 88 Configuring your instance
Lecture 89 Creating and sharing AMIs
Lecture 90 Copying AMIs
Lecture 91 Working with AMIs
Lecture 92 Monitoring an EC2 Instance
Lecture 93 EC2 Monitoring Lab
Lecture 94 Using CloudTrail to Audit Users
Section 8: Data Structure and Types
Lecture 95 Data Variety Problem: Source Data Storage
Lecture 96 Structured Data Stores
Lecture 97 Introduction to semi-structured and unstructured data stores
Lecture 98 AWS RDS
Section 9: Veracity Cleansing and Data Transformation
Lecture 99 Data Veracity
Lecture 100 Common Data Issues
Lecture 101 Database Consistency
Lecture 102 AWS ElasticCache
Lecture 103 AWS AppStream
Lecture 104 AWS GuardDuty
Section 10: Reporting and Business Intelligence
Lecture 105 Value in Data Analysis Solution
Lecture 106 Types of Analytics
Lecture 107 Visualizing Data
Lecture 108 Creating Your First Visual With AWS QuickSight
Lecture 109 AWS UI Hub
Lecture 110 Uploading Data Set to S3
Lecture 111 Creating Database and Tables
Lecture 112 Making Connection AWS Athena to AWS QuickSight
Lecture 113 AWS Sample Dataset
Lecture 114 Upgrading AWS QuickSight to Enterprise and VPC
Lecture 115 Importing CSV Data
Lecture 116 AWS RDS Connection to AWS QuickSight
Section 11: Domain 4: Data Security and Governance (18% of scored content)
Lecture 117 Principle of Least Privilege as it applies to AWS Security
Lecture 118 AWS Virtual Private Cloud (VPC) Introduction
Lecture 119 Understanding Amazon VPC and Subnets
Lecture 120 How to Create AWS VPC Hands-on Lab
Lecture 121 VPC Security Networking Components
Lecture 122 VPC Security
Lecture 123 Difference Between Managed Services and Unmanaged Services
Lecture 124 What is AWS IAM?
Lecture 125 IAM Roles and Policies
Lecture 126 IAM Users and Groups
Lecture 127 IAM Federated Users and Best Practices
Lecture 128 IAM Design Principles
Lecture 129 CloudWatch
Lecture 130 CloudTrail
Section 12: Conclusion
Lecture 131 Key Takeaways
Section 13: Practice Exam Questions
Section 14: Practice Exam #2
Section 15: Resources
Lecture 132 AWS Certified Data Engineer Exam Guide
Lecture 133 Download Resources
Section 16: Additional Key Topics and Readings
Lecture 134 Amazon EventBridge
Lecture 135 Amazon Macie
Lecture 136 How to Determine DPU Capacity?
Lecture 137 Amazon SQS
Lecture 138 Apache Hive on AWS
Lecture 139 Data filters in Lake Formation
Lecture 140 What is a Data Share? Amazon RedShift Data Share
Lecture 141 How to Rotate AWS Secrets Manager secrets
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What you'll learn
Understanding AWS data storage options: Amazon S3, RDS, DynamoDB
Ingest and transform data, and orchestrate data pipelines while applying programming concepts.
Choose an optimal data store, design data models, catalog data schemas, and manage data lifecycles.
Operationalize, maintain, and monitor data pipelines. Analyze data and ensure data quality
Implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues
Working with AWS Data Pipeline for data movement and processing
Key concepts of AWS Glue for ETL processes
Querying data in S3 using AWS Athena
Requirements
An understanding of the AWS services for encryption, governance, protection, and logging of all data that is part of data pipelines
The ability to compare AWS services to understand the cost, performance, and functional differences between services
AWS Foundational knowledge of services
General concepts for networking, storage, and compute
Description
The AWS Certified Data Engineer - Associate (DEA-C01) exam validates a candidate's ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices.[v2024: This course is based on the current beta exam and the official exam guide. We'll keep it updated as final exams are released by AWS. Happy learning]You should have the equivalent of 2–3 years of experience in data engineering. The target candidate should understand the effects of volume, variety, and velocity on data ingestion, transformation, modeling, security, governance, privacy, schema design, and optimal data store design. Additionally, the target candidate should have at least 1–2 years of hands-on experience with AWS services.Why should you get AWS Certified?Getting AWS Certified can help you propel your career, whether you're looking to find a new role, showcase your skills to take on a new project, or become your team's go-to expert. And because AWS Certification exams are created by experts in the relevant role or technical area, preparing for one of these exams helps you build the required skills identified by skilled practitioners in the field.See what our students say "It is such a comprehensive course that I don't need to take any other course but this one to learn all important concepts and hand-on application with this AWS Certified Data Engineer - Associate course, and I would without a doubt recommend it to everyone." - Martha Jones"This is such an awesome course. Clear instruction, and I loved every bit of it – Wonderful learning experience!" Carlos Nelson.Join thousands of other students and share valuable experience.This course also comes with:Lifetime access to all future updatesA responsive instructor in the Q&A SectionUdemy Certificate of Completion Ready for DownloadA 30 Day "No Questions Asked" Money Back Guarantee!FREE AWS Certified Data Engineer- Associate quizzes and sample exam within this course.FREE E-Book on AWS Cost OptimizationWhy take this course?As 8x AWS, Microsoft, and Cisco Certified, a senior Enterprise Architect & Project Manager managing and deploying enterprise level IT projects, my experience with AWS has been phenomenally great! I am excited to share my knowledge and transfer skills to my students. Enroll now in AWS Certified Data Engineer - Associate (DEA-C01) course today and revolutionize your learning. Stay at the cutting edge of certification and AWS architectures- and enjoy bigger, brighter opportunities.See you in class.Syed Team ClayDesk
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Course Structure and Agenda
Lecture 3 Important Note
Lecture 4 Day-to-Day Activities of an AWS Data Engineer
Lecture 5 Note Taking
Lecture 6 The Value of AWS Certified Data Engineer
Lecture 7 What is Data Analytics and Data Analysis Solutions
Lecture 8 How to Create S3 Bucket with Amazon Q and New AWS Management Console
Lecture 9 Challenges of Data Analytics
Section 2: Data Ingestion and Transformation (34% of scored content)
Lecture 10 Throughput VS Latency
Lecture 11 Replayability, Stateful Vs Stateless Transactions
Lecture 12 ETL Process
Lecture 13 AWS Step Functions Use Cases Architectures
Lecture 14 Exercise: AWS Step Functions
Lecture 15 AWS Step Functions Workshop
Lecture 16 AWS Athena
Lecture 17 What is Kubernetes?
Lecture 18 How to Create Kubernetes Cluster?
Lecture 19 Cloud VS Distributed Computing
Lecture 20 Common Data Transformation Issues and Debugging
Lecture 21 Understanding DevOps
Lecture 22 Continuous Integration Continuous Delivery
Lecture 23 CICD Difference
Lecture 24 What is Fan-in Fan-out in Stream Data Distribution
Lecture 25 Understanding Even Driven Architecture
Lecture 26 How to configure AWS services for data pipelines?
Section 3: Cloud Data Migration
Lecture 27 Cloud Migration Benefits
Lecture 28 Cloud Migration Strategies
Lecture 29 Cloud Migration Process
Lecture 30 AWS Migration Hub
Lecture 31 Discovering your network infrastructure
Lecture 32 Migrating your network infrastructure
Lecture 33 Amazon EC2 recommendations
Lecture 34 Migration acceleration program
Lecture 35 AWS managed services
Lecture 36 AWS Cloud data migration services
Lecture 37 Online and offline data migration
Lecture 38 Server migration service
Lecture 39 How database migration service works
Lecture 40 Database migration use cases
Lecture 41 AWS Schema conversion tool
Lecture 42 Sample database migration to AWS
Lecture 43 Database migration best practices
Section 4: Domain 2: Data Store Management (26% of scored content)
Lecture 44 Data Volume
Lecture 45 Types of Data
Lecture 46 AWS S3 Storage Explained
Lecture 47 How to Create Amazon S3 Bucket
Lecture 48 Create S3 Bucket and Cross Region Replication
Lecture 49 Introduction to Data Lakes Architecture
Lecture 50 AWS Data Lake In-Depth
Lecture 51 AWS Glue - AWS Athena
Lecture 52 Data Storage Methods
Lecture 53 Data Warehouses
Lecture 54 Amazon RDS
Lecture 55 Amazon DynamoDB
Lecture 56 AWS DynamoDB Hands-on Lab
Lecture 57 Amazon SageMaker
Section 5: AWS Sage Maker and Machine Learning
Lecture 58 The AWS Machine Learning Service
Lecture 59 First steps in building a ML Model
Lecture 60 Understanding AWS Datasources
Lecture 61 ML Training Models
Lecture 62 Importance of Feature Transformation
Lecture 63 Evaluating Models
Lecture 64 Preparing data for Machine Learning
Lecture 65 Creating a datasource and model in AWS
Lecture 66 Serverless ML Inference with AWS Lambda
Lecture 67 What is SageMaker Revisited
Lecture 68 Setting up AWS to use SageMaker
Lecture 69 Machine Learning in SageMaker
Lecture 70 Intro to Linear Learner
Lecture 71 Preparing data for Linear Learner algorithm
Lecture 72 Training data using Linear Learner
Lecture 73 Creating a hyperparameter tuning job
Section 6: Domain 3: Data Operations and Support (22% of scored content) Velocity Data
Lecture 74 Batch Data Processing
Lecture 75 Batch Processing Architecture
Lecture 76 Velocity of Data Challenges
Lecture 77 Stream Data Processing
Section 7: AWS EC2 Deep Dive
Lecture 78 EC2 Basic Infrastructure
Lecture 79 Viewing your service limits
Lecture 80 Instance lifecycle
Lecture 81 Instance Types
Lecture 82 Launching your first instance
Lecture 83 Working with launch templates
Lecture 84 Launching an instance from an existing instance
Lecture 85 Instance states
Lecture 86 Connecting to a Windows Instance
Lecture 87 Connecting to a Linux Instance
Lecture 88 Configuring your instance
Lecture 89 Creating and sharing AMIs
Lecture 90 Copying AMIs
Lecture 91 Working with AMIs
Lecture 92 Monitoring an EC2 Instance
Lecture 93 EC2 Monitoring Lab
Lecture 94 Using CloudTrail to Audit Users
Section 8: Data Structure and Types
Lecture 95 Data Variety Problem: Source Data Storage
Lecture 96 Structured Data Stores
Lecture 97 Introduction to semi-structured and unstructured data stores
Lecture 98 AWS RDS
Section 9: Veracity Cleansing and Data Transformation
Lecture 99 Data Veracity
Lecture 100 Common Data Issues
Lecture 101 Database Consistency
Lecture 102 AWS ElasticCache
Lecture 103 AWS AppStream
Lecture 104 AWS GuardDuty
Section 10: Reporting and Business Intelligence
Lecture 105 Value in Data Analysis Solution
Lecture 106 Types of Analytics
Lecture 107 Visualizing Data
Lecture 108 Creating Your First Visual With AWS QuickSight
Lecture 109 AWS UI Hub
Lecture 110 Uploading Data Set to S3
Lecture 111 Creating Database and Tables
Lecture 112 Making Connection AWS Athena to AWS QuickSight
Lecture 113 AWS Sample Dataset
Lecture 114 Upgrading AWS QuickSight to Enterprise and VPC
Lecture 115 Importing CSV Data
Lecture 116 AWS RDS Connection to AWS QuickSight
Section 11: Domain 4: Data Security and Governance (18% of scored content)
Lecture 117 Principle of Least Privilege as it applies to AWS Security
Lecture 118 AWS Virtual Private Cloud (VPC) Introduction
Lecture 119 Understanding Amazon VPC and Subnets
Lecture 120 How to Create AWS VPC Hands-on Lab
Lecture 121 VPC Security Networking Components
Lecture 122 VPC Security
Lecture 123 Difference Between Managed Services and Unmanaged Services
Lecture 124 What is AWS IAM?
Lecture 125 IAM Roles and Policies
Lecture 126 IAM Users and Groups
Lecture 127 IAM Federated Users and Best Practices
Lecture 128 IAM Design Principles
Lecture 129 CloudWatch
Lecture 130 CloudTrail
Section 12: Conclusion
Lecture 131 Key Takeaways
Section 13: Practice Exam Questions
Section 14: Practice Exam #2
Section 15: Resources
Lecture 132 AWS Certified Data Engineer Exam Guide
Lecture 133 Download Resources
Section 16: Additional Key Topics and Readings
Lecture 134 Amazon EventBridge
Lecture 135 Amazon Macie
Lecture 136 How to Determine DPU Capacity?
Lecture 137 Amazon SQS
Lecture 138 Apache Hive on AWS
Lecture 139 Data filters in Lake Formation
Lecture 140 What is a Data Share? Amazon RedShift Data Share
Lecture 141 How to Rotate AWS Secrets Manager secrets
Anyone who wants to get AWS Certified Data Engineer Associate certification,Beginner who wants to get into cloud computing and get AWS certified
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