Exam Readiness: AWS Certified Machine Learning - Specialty (ERMLS)

Detailed Course Outline

Day One

Module 0: Course Introduction

Module 1: Exam Overview and Test-taking Strategies

• Exam overview, logistics, scoring, and user interface
• Question mechanics and design
• Test-taking strategies

Module 2: Domain 1: Data Engineering

• Domain 1.1: Data Repositories for machine learning
• Domain 1.2: Identify and implement a data-ingestion solution
• Domain 1.3: Identify and implement a data-transformation solution
• Walkthrough of study questions
• Domain 1 quiz

Module 3: Domain 2: Exploratory Data Analysis

• Domain 2.1: Sanitize and prepare data for modeling
• Domain 2.2: Perform featuring engineering
• Domain 2.3: Analyze and visualize data for ML
• Walkthrough of study questions
• Domain 2 quiz

Module 4: Domain 3: Modeling

• Domain 3.1: Frame business problems as machine learning (ML) problems
• Domain 3.2: Select the appropriate model(s) for a given ML problem
• Domain 3.3: Train ML models
• Domain 3.4 Perform hyperparameter optimization
• Domain 3.5 Evaluate ML models
• Walkthrough of study questions
• Domain 3 quiz

Module 5: ML Implementation and Operations

• Domain 4.1: Build ML solutions for performance, availability, scalability, resiliency, and fault tolerance
• Domain 4.2: Recommend and implement the appropriate ML services and features for a given problem
• Domain 4.3: Apply basic AWS security practices to ML solutions
• Domain 4.4: Deploy and operationalize ML solutions
• Walkthrough of study questions
• Domain 4 quiz

Module 6: Comprehensive study questions

Module 7: Study Material

Module 8: Wrap-up