Become an AWS Certified Data Engineer

Become an AWS Certified Data Engineer, available at $19.99, has an average rating of 4.35, with 141 lectures, 2 quizzes, based on 12 reviews, and has 159 subscribers.

You will learn about 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 This course is ideal for individuals who are Anyone who wants to get AWS Certified Data Engineer Associate certification or Beginner who wants to get into cloud computing and get AWS certified It is particularly useful for Anyone who wants to get AWS Certified Data Engineer Associate certification or Beginner who wants to get into cloud computing and get AWS certified.

Enroll now: Become an AWS Certified Data Engineer

Summary

Title: Become an AWS Certified Data Engineer

Price: $19.99

Average Rating: 4.35

Number of Lectures: 141

Number of Quizzes: 2

Number of Published Lectures: 141

Number of Published Quizzes: 2

Number of Curriculum Items: 143

Number of Published Curriculum Objects: 143

Number of Practice Tests: 2

Number of Published Practice Tests: 2

Original Price: $64.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Anyone who wants to get AWS Certified Data Engineer Associate certification
Beginner who wants to get into cloud computing and get AWS certified

Target Audiences

Anyone who wants to get AWS Certified Data Engineer Associate certification
Beginner who wants to get into cloud computing and get AWS certified

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.

Course Description

This course covers all aspects of the following domain areas:

Domain 1: Data Ingestion and Transformation (34% of scored content)
Domain 2: Data Store Management (26% of scored content)
Domain 3: Data Operations and Support (22% of scored content)
Domain 4: Data Security and Governance (18% of scored content)

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 thisAWS Certified Data Engineer – Associatecourse, 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 updates
A responsive instructor in the Q&A Section
Udemy Certificate of Completion Ready for Download
A 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 Optimization

Why 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

Course Curriculum

Chapter 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

Chapter 2: Data Ingestion and Transformation (34% of scored content)

Lecture 1: Throughput VS Latency

Lecture 2: Replayability, Stateful Vs Stateless Transactions

Lecture 3: ETL Process

Lecture 4: AWS Step Functions Use Cases Architectures

Lecture 5: Exercise: AWS Step Functions

Lecture 6: AWS Step Functions Workshop

Lecture 7: AWS Athena

Lecture 8: What is Kubernetes?

Lecture 9: How to Create Kubernetes Cluster?

Lecture 10: Cloud VS Distributed Computing

Lecture 11: Common Data Transformation Issues and Debugging

Lecture 12: Understanding DevOps

Lecture 13: Continuous Integration Continuous Delivery

Lecture 14: CICD Difference

Lecture 15: What is Fan-in Fan-out in Stream Data Distribution

Lecture 16: Understanding Even Driven Architecture

Lecture 17: How to configure AWS services for data pipelines?

Chapter 3: Cloud Data Migration

Lecture 1: Cloud Migration Benefits

Lecture 2: Cloud Migration Strategies

Lecture 3: Cloud Migration Process

Lecture 4: AWS Migration Hub

Lecture 5: Discovering your network infrastructure

Lecture 6: Migrating your network infrastructure

Lecture 7: Amazon EC2 recommendations

Lecture 8: Migration acceleration program

Lecture 9: AWS managed services

Lecture 10: AWS Cloud data migration services

Lecture 11: Online and offline data migration

Lecture 12: Server migration service

Lecture 13: How database migration service works

Lecture 14: Database migration use cases

Lecture 15: AWS Schema conversion tool

Lecture 16: Sample database migration to AWS

Lecture 17: Database migration best practices

Chapter 4: Domain 2: Data Store Management (26% of scored content)

Lecture 1: Data Volume

Lecture 2: Types of Data

Lecture 3: AWS S3 Storage Explained

Lecture 4: How to Create Amazon S3 Bucket

Lecture 5: Create S3 Bucket and Cross Region Replication

Lecture 6: Introduction to Data Lakes Architecture

Lecture 7: AWS Data Lake In-Depth

Lecture 8: AWS Glue – AWS Athena

Lecture 9: Data Storage Methods

Lecture 10: Data Warehouses

Lecture 11: Amazon RDS

Lecture 12: Amazon DynamoDB

Lecture 13: AWS DynamoDB Hands-on Lab

Lecture 14: Amazon SageMaker

Chapter 5: AWS Sage Maker and Machine Learning

Lecture 1: The AWS Machine Learning Service

Lecture 2: First steps in building a ML Model

Lecture 3: Understanding AWS Datasources

Lecture 4: ML Training Models

Lecture 5: Importance of Feature Transformation

Lecture 6: Evaluating Models

Lecture 7: Preparing data for Machine Learning

Lecture 8: Creating a datasource and model in AWS

Lecture 9: Serverless ML Inference with AWS Lambda

Lecture 10: What is SageMaker Revisited

Lecture 11: Setting up AWS to use SageMaker

Lecture 12: Machine Learning in SageMaker

Lecture 13: Intro to Linear Learner

Lecture 14: Preparing data for Linear Learner algorithm

Lecture 15: Training data using Linear Learner

Lecture 16: Creating a hyperparameter tuning job

Chapter 6: Domain 3: Data Operations and Support (22% of scored content) Velocity Data

Lecture 1: Batch Data Processing

Lecture 2: Batch Processing Architecture

Lecture 3: Velocity of Data Challenges

Lecture 4: Stream Data Processing

Chapter 7: AWS EC2 Deep Dive

Lecture 1: EC2 Basic Infrastructure

Lecture 2: Viewing your service limits

Lecture 3: Instance lifecycle

Lecture 4: Instance Types

Lecture 5: Launching your first instance

Lecture 6: Working with launch templates

Lecture 7: Launching an instance from an existing instance

Lecture 8: Instance states

Lecture 9: Connecting to a Windows Instance

Lecture 10: Connecting to a Linux Instance

Lecture 11: Configuring your instance

Lecture 12: Creating and sharing AMIs

Lecture 13: Copying AMIs

Lecture 14: Working with AMIs

Lecture 15: Monitoring an EC2 Instance

Lecture 16: EC2 Monitoring Lab

Instructors

Syed Raza
Best Selling Instructor, Enterprise Architect, 8x AWS, PhD
ClayDesk E-learning
The Knowledge Factory

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 2 votes
4 stars: 5 votes
5 stars: 5 votes

Frequently Asked Questions

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