Core AWS Services

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Core AWS Services

Coursera · Beginner ·🔍 RAG & Vector Search ·1mo ago
Master essential AWS services and gain practical, hands-on skills to design, deploy, and manage cloud solutions confidently. Start with EC2 basics, then move on to AMIs, public vs private IPs, elastic IPs, AWS storage ( discussing S3 & in-depth looking at S3 encryption, CloudFront-CDN & Glacier ), understand scalable storage solutions for your data, and explore Content delivery systems/ Data Protection. Laying the Groundwork: Establish a solid cloud network by mastering Route53, DNS, health checks, DNS resolution, and VPC/Subnet/ACLs at an architectural level to design secure and scalable cloud networks. Finally, you’ll delve into AWS databases (RDS, Aurora with read replicas, Redshift, ElastiCache) and AWS DMS to handle data at scale. By the end of it, you will feel like a high-performance cloud specialist and nothing's cooler than that! Ready to take on an AWS project and become a sought-after IT professional? Enroll now to begin your cloud career! Disclaimer: AWS and Amazon Web Services are trademarks of Amazon.com, Inc. or its affiliates. This course is not affiliated with or endorsed by AWS.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

What Enterprise RAG Is Ready For Today and What Production Deployment Actually Requires
Learn what enterprise RAG is ready for today and what production deployment actually requires, to successfully implement RAG in your organization
Dev.to · Manjunath
I Built GraphRAG From Scratch — Then a December 2025 Paper Made It Look Basic
Learn about HGMem, a new RAG architecture that overcomes limitations of binary graphs, and how it compares to GraphRAG
Medium · RAG
When Should You Use Text2Cypher in a GraphRAG Pipeline
Learn when to use Text2Cypher in a GraphRAG pipeline to retrieve precise graph results from natural language questions
Dev.to AI
How to build a production RAG pipeline in Python (without a vector database)
Learn to build a production-ready RAG pipeline in Python without relying on a vector database, and understand the key considerations for a scalable and efficient implementation
Dev.to · Ayi NEDJIMI
Up next
Watch this before applying for jobs as a developer.
Tech With Tim
Watch →