Cloud Data Architect's Guide to MLOps Pipeline Design on AWS
Master the design and implementation of scalable, automated, and cost-effective MLOps pipelines on AWS, tailored for Cloud Data Architects.
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Foundations of MLOps and Data Pipeline Design on AWS
Unit 1: MLOps Fundamentals and AWS Overview
MLOps vs. DevOps
MLOps Lifecycle Stages
AWS for MLOps: An Intro
Unit 2: Data Ingestion and Storage on AWS
Data Ingestion Strategies
S3: The Data Lake Core
Data Versioning & Governance
Unit 3: Data Preparation and Feature Engineering
Data Prep with AWS Glue
Feature Engineering on AWS
Data Quality & Validation
Automating, Deploying, and Monitoring MLOps Pipelines on AWS
Unit 1: Building Automated ML CI/CD Pipelines
CI/CD for ML Models
CodePipeline & CodeBuild
SageMaker Pipelines
Unit 2: Strategies for Model Deployment
Real-time Model Serving
Batch Model Serving
Containerized Deployments
Unit 3: Monitoring ML Models in Production
Model Monitoring Basics
AWS Monitoring Tools