📅 30-Day MLA-C01 Study Plan

A steady month-long plan covering the current four-domain MLA-C01 outline.

Prerequisites

  • Basic Python and ML concepts
  • Beginner AWS knowledge
  • 1-2 hours of study time per day

Study Schedule

Week 1 (Days 1-7)Data Preparation for Machine Learning
  • Days 1-2: S3, data formats, partitioning, lifecycle, encryption, and dataset organization
  • Days 3-4: Glue, Athena, DataBrew, processing jobs, and transformation workflows
  • Day 5: Feature engineering, Feature Store, leakage prevention, and data quality
  • Days 6-7: Domain 1 practice quiz, cheat sheet review, and flashcards
Week 2 (Days 8-14)ML Model Development
  • Days 8-9: Algorithm selection and use cases
  • Days 10-11: SageMaker training jobs, built-in algorithms, containers, and distributed training
  • Day 12: Hyperparameter tuning and cost-aware training
  • Days 13-14: Evaluation metrics, model registry, and Domain 2 practice
Week 3 (Days 15-21)Deployment and Orchestration
  • Days 15-16: Inference options and endpoint deployment patterns
  • Day 17: Endpoint autoscaling, variants, rollback, and production release controls
  • Days 18-19: SageMaker Pipelines, workflow steps, CI/CD, and model approval
  • Days 20-21: Domain 3 practice and deployment flashcards
Week 4 (Days 22-28)Monitoring, Maintenance, Security, and Full Exams
  • Days 22-23: Model Monitor, baselines, drift types, and CloudWatch observability
  • Days 24-25: IAM, KMS, VPC endpoints, private training, private inference, and audit controls
  • Day 26: Full mock exam #1
  • Day 27: Review mock exam #1 and rebuild weak notes
  • Day 28: Full mock exam #2
Days 29-30Final Review
  • Review all four official MLA-C01 domains and weights
  • Rerun weak-domain flashcards
  • Review inference choices, monitoring types, and metric selection
  • Rest and keep notes concise

Study Tips

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Build comparison tables for inference options, model metrics, and monitoring types.

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Write down why wrong answers are wrong; MLA-C01 distractors are often plausible service choices.

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Spend extra review time on SageMaker Pipelines, Model Registry, Model Monitor, and Feature Store.

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Aim for consistent 80%+ on mixed practice before scheduling.

Ready to Practice?

Put your study plan into action with MLA-C01 practice questions.

Other Study Plans