Course Description:
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.
Key Components:
a. S3
b. Redshift
Project 5: Conditional Workflow State Machine The fifth project involves the creation of an AWS Step Functions state machine that not only performs basic arithmetic but also orchestrates intricate conditional workflows based on the outcome. It’s a deep dive into building conditional workflows using AWS Step Functions.
Key Components:
a. Step Function
b. Lambda
Project 6: Real-time IoT Data Ingestion and Analysis with AWS Kinesis and IoT Core Project 6 offers an end-to-end exploration of real-time IoT data ingestion utilizing AWS Kinesis and AWS IoT Core. You will configure IoT devices, stream data to AWS, and archive this data in an S3 bucket.
Key Components:
a. IoT Core
b. Kinesis Firehose
c. S3
d. Lambda
Project 7: Seamless On-Premises to AWS RDS Database Migration with AWS DMS The final project is centered around the seamless migration of an on-premises database to an AWS Relational Database Service (RDS) instance, all orchestrated by the AWS Database Migration Service (DMS). This migration promises improved data management, scalability, and availability while prioritizing data integrity and minimizing business disruptions.
Key Components:
a. RDS
b. DMS
c. EC2
d. SSMS
Who Should Enroll:
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Aspiring Cloud Enthusiasts
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Developers Exploring AWS
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Business Professionals Interested in Cloud Technology
Prerequisites:
No prior experience with AWS is mandatory, although a basic understanding of programming concepts will be advantageous.
What You’ll Gain:
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Hands-on Experience with AWS Services
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Practical Skills in Building Real-World AWS Projects
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Insights into Cloud-Based Data Processing and Analysis
Embark on this enriching journey to explore AWS through hands-on projects, and equip yourself with the knowledge and skills needed to embark on your cloud computing adventure!
Lessons:
