AWS Certified Machine Learning - Specialty

Technology Coverage

Industry Trends

• Trend: Foundation Models and LLMs; Description: Shift from custom ML models to leveraging pre-trained foundation models for many use cases; Impact On Exam: Increased focus on understanding when to use foundation models vs custom models, fine-tuning strategies, and prompt engineering
• Trend: MLOps Maturity; Description: Growing emphasis on operationalizing ML with automated pipelines, monitoring, and governance; Impact On Exam: Domain 4 (MLOps) becoming more critical with tools like SageMaker Pipelines, Model Monitor, and Feature Store
• Trend: Democratization of ML; Description: No-code/low-code ML tools (like SageMaker Canvas) making ML accessible to non-technical users; Impact On Exam: Understanding when to recommend no-code vs traditional ML approaches
• Trend: Cost Optimization Focus; Description: Organizations increasingly focused on optimizing ML training and inference costs; Impact On Exam: More questions on Spot Instances, rightsizing, and cost-performance tradeoffs
• Trend: Responsible AI; Description: Growing emphasis on bias detection, model explainability, and responsible AI practices; Impact On Exam: SageMaker Clarify for bias detection and explainability increasingly relevant