Course Outline

Introduction

  • Understanding Machine Learning with SageMaker for Government
  • Machine Learning Algorithms for Government Applications

Overview of AWS SageMaker Features

  • AWS and Cloud Computing for Government
  • Model Development for Government Projects

Setting up AWS SageMaker for Government

  • Creating an AWS Account for Government Use
  • Configuring IAM Admin User and Group for Government Security

Familiarizing with SageMaker Studio for Government Users

  • User Interface Overview for Government Personnel
  • Using Studio Notebooks for Government Data Analysis

Preparing Data Using Jupyter Notebooks for Government Projects

  • Notebooks and Libraries for Government Data Processing
  • Creating a Notebook Instance for Government Use

Training a Model with SageMaker for Government Applications

  • Training Jobs and Algorithms for Government Models
  • Data and Model Parallel Training for Government Scalability
  • Post-Training Bias Analysis for Government Fairness and Accountability

Deploying a Model in SageMaker for Government Operations

  • Model Registry and Model Monitor for Government Compliance
  • Compiling and Deploying Models with Neo for Government Efficiency
  • Evaluating Model Performance for Government Decision-Making

Cleaning Up Resources for Government Projects

  • Deleting Endpoints for Government Resource Management
  • Deleting Notebook Instances for Government Cost Control

Troubleshooting for Government Users

Summary and Conclusion for Government Applications

Requirements

  • Experience in application development for government projects
  • Familiarity with the Amazon Web Services (AWS) Console

Audience

  • Data scientists
  • Developers
 21 Hours

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