AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 4 Machine Learning Implementation and Operations

AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 4 Machine Learning Implementation and Operations

26mIntermediate2023-03-01

Authors

Noah Gift

Noah Gift

MLOps Expert | Solopreneur | Author | Adjunct Professor | CTO

Course details

Join MLOps expert and CTO Noah Gift to learn all about data engineering and prepare for the machine learning implementation and operations portion of the AWS Certified Machine Learning – Specialty (MLS-C01) certification. This domain involves building machine learning solutions that are performance, available, scalability, resiliency, and fault tolerant. Noah explains using AWS environment logging and monitoring, building error monitoring, and using multiple regions and multiple AZs. He goes over how to use AMI/golden images and docker containers. Noah covers auto-scaling groups, as well as rightsizing instances, volumes, and provisioned IOPS. Plus, he shows you how to use load balancing and follow AWS best practices.

Skills covered

Machine LearningAmazon Web Services (AWS)AmazonCloud ServicesCloud PlatformsArtificial Intelligence (AI)Cert PrepCloud Computing

Concepts

Introduction

  • Overview

Build ML Solutions for Performance, Availability, Scalability, Resiliency, and Fault

  • AWS environment logging and monitoring
  • Multiple regions, multiple AZs
  • Reproducible workflows
  • AWS flavored DevOps

Recommend and Implement the Appropriate ML Services and Features for a Given Problem

  • Provisioning EC2
  • Compute choices
  • Provisioning EBS
  • AWS AI machine learning services

Apply Basic AWS Security Practices to Machine Learning Solutions

  • Principle of least privilege (PLP)
  • Integrated security

Deploy and Operationalize Machine Learning Solutions

  • SageMaker workflow
  • Predictions with SageMaker Canvas
  • Retraining models

Conclusion

  • Summary