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| File Name: | [AWS Projets ]- 7 AWS Projects to Supercharge Your Portfolio |
| Content Source: | https://www.udemy.com/course/aws-projets-7-aws-projects-to-supercharge-your-portfolio/ |
| Genre / Category: | Other Tutorials |
| File Size : | 1.8GB |
| Publisher: | udemy |
| Updated and Published: | November 20, 2023 |
[AWS Projets ]- Accelerate Your Amazon Web Services (AWS) Mastery: Dive into Hands-On Projects for Cloud Expertise!
Welcome to the “Top 7 Projects for Beginners,” an immersive series of projects meticulously designed to provide you with invaluable hands-on experience and expertise in AWS cloud services. This course is tailored to be an ideal launchpad for beginners keen on delving into the dynamic realm of cloud computing and AWS.
Project 1: File Upload Notification System In this inaugural project, you will construct a sophisticated system that monitors an S3 bucket for newly uploaded files. It seamlessly triggers a Lambda function to process these files, sends out notifications using SNS, and diligently stores essential metadata in an SQS queue for subsequent processing.
Key Focus Areas:
a. S3 Event Trigger
b. Lambda
c. SQS
d. SNS
e. Integration of S3 with other services
Project 2: Serverless Data Analysis Platform Project 2 revolves around crafting a cutting-edge serverless data analysis platform. It empowers Lambda functions to access and analyze data from both a public RDS database and a private RDS database, with the results elegantly stored in an S3 bucket.
Key Components:
a. RDS
b. Lambda
c. S3
d. VPC and subnets
Project 3: Sales Analytics Dashboard for Global Energy Industry In the third project, you will embark on the journey of developing a comprehensive dashboard using Amazon QuickSight, which will provide invaluable insights into sales based on various attributes.
Key Component:
a. QuickSight
Project 4: Data Ingestion and Extraction Pipeline for Redshift Project 4 is all about constructing a robust data pipeline that facilitates seamless data loading from Amazon S3 into Amazon Redshift. This pipeline boasts the ability to handle both compressed and uncompressed files, unload encrypted data files from Redshift back to S3, and offers the flexibility to unload data in delimited or fixed-width formats as needed.
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