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GitHub: https://github.com/knodax-labs-demo/aws-data-and-ml-labs/blob/main/05-s3-secure-data-repository-lab.md Designing Data Repositories and Storage-Solutions for ML and DE In this step-by-step hands-on lab, you’ll learn how to design secure, cost-optimized, and access-controlled S3 data repositories — a must-have skill for data engineering and machine learning workflows on AWS. We’ll walk through how to configure IAM access policies, enable server-side encryption, enable versioning, set lifecycle policies to transition data to Glacier, and analyze storage costs using AWS Cost Explorer. ⚠️ Important: S3 is not free beyond the Free Tier. You may be charged for storage, API requests, and other operations depending on your usage. If you prefer not to incur any charges, you can simply watch this tutorial without following along in your own AWS account. 🔍 What You’ll Learn: Create and configure an S3 bucket for ML data storage Set up IAM policies for secure read/write access Enable server-side encryption (SSE-S3) for data protection Turn on bucket versioning and configure lifecycle policies to Glacier Use Cost Explorer to review storage costs and optimize data lifecycle By the end of this video, you’ll understand how to build secure, scalable, and cost-efficient S3 repositories — an essential skill for AWS Certified Data Engineer – Associate (DEA-C01) and Machine Learning – Specialty (MLS-C01) exam preparation. 📚 More AWS Tutorials & Exam Prep: 👉 Subscribe to the KnoDAX YouTube channel for more AWS hands-on labs, certification guides, and real-world projects. 👉 Explore our complete collection of AWS certification books and study guides: https://www.amazon.com/stores/SK-Singh/author/B09L6H39XM #AWSS3 #AWSTutorial #DataStorage #CloudComputing #DataEngineer #MachineLearning #KnoDAX #AWSCertification #ServerSideEncryption #Glacier #CostOptimization
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