AWS Certified Machine Learning Engineer - Associate (MLA-C01): ML Model Development

Overview

AWS has a broad range of machine learning services to help businesses approach complex problems. In this course, AWS Certified Machine Learning Engineer - Associate (MLA-C01):

ML Model Development, you’ll learn to navigate these services and select the approach that is most appropriate for your machine learning (ML) solutions.

First, you’ll explore AWS managed ML and AI services that are purpose-built for specific use cases. Next, you’ll discover built-in algorithms to tackle more complex ML challenges using Amazon SageMaker.

Finally, you’ll learn how to monitor your models and make adjustments throughout training. When you’re finished with this course, you’ll have the skills and knowledge of machine learning engineering on AWS needed to pass this domain of the exam.

Syllabus

• Introduction to AWS Machine Learning Services
Overview of AWS Machine Learning Offerings
Identifying Suitable AWS Services for ML Solutions
• AWS Managed ML and AI Services
Amazon Rekognition
Amazon Comprehend
Amazon Polly
Amazon Lex
Use Cases and Examples
• Amazon SageMaker
Setting Up Amazon SageMaker Environment
SageMaker Studio and Notebooks
Built-in Algorithms
Linear Learner
XGBoost
K-Means Clustering
Hyperparameter Optimization
• Building and Training ML Models
Data Preparation and Processing
Feature Engineering on AWS
Training Models in SageMaker
Distributed Training with SageMaker
• Model Evaluation and Deployment
Evaluating Model Performance
A/B Testing and Model Validation
Deploying Models with Amazon SageMaker Endpoints
• Monitoring and Maintenance
Model Monitoring with Amazon SageMaker Model Monitor
Automating Retraining and Deployment with Pipelines
Handling Model Drift and Retraining
• Exam Preparation
Review of Key Concepts
Exam Strategies and Practice Questions
Additional Resources for Study
• Conclusion and Next Steps
Summary of AWS ML Services
Advanced Learning Paths in AWS Machine Learning

Taught by

David Blocher

Subjects

Programming