AWS Certified AI Practitioner

Study plan

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How to Pass the AWS Certified AI Practitioner Exam

AIF-C01

A study plan for the AWS Certified AI Practitioner certification exam, built from the official domain weights instead of a generic template. Start with official AWS Skill Builder digital training, especially the exam prep course. Use AWS Free Tier to get hands-on with SageMaker and AI services. Practice building end-to-end ML pipelines. Review the exam guide extensively, focusing on domain weights. Use practice tests to identify weak areas. Revise key ML metrics (precision, recall, F1) and service use cases. Allocate 60% study time to hands-on labs and 40% to theory.

5 domains
65 questions
90 min
70% to pass

Study in weight order, not topic order

The plan below follows the official blueprint weights, so the order of study is the order that returns the most points.

  1. 1

    ML Model Development

    24%
    • Select appropriate algorithms for given business problems
    • Implement training pipelines using Amazon SageMaker
    • Perform hyperparameter tuning and model optimization
    • Evaluate model performance (e.g., accuracy, precision, recall, F1 score, confusion matrix)
    • +1 more topics in the blueprint

    16 practice questions tagged to this domain.

  2. 2

    AI and ML Services on AWS

    24%
    • Leverage pre-built AI services (e.g., Amazon Rekognition, Amazon Comprehend, Amazon Polly, Amazon Transcribe, Amazon Translate)
    • Use Amazon SageMaker for custom model development
    • Explore AWS AI services for business applications (e.g., Amazon Personalize, Amazon Forecast)
    • Understand AWS AI security, compliance, and governance

    15 practice questions tagged to this domain.

  3. 3

    Fundamentals of AI and ML

    20%
    • Define basic AI and ML terms (e.g., supervised learning, unsupervised learning, reinforcement learning)
    • Identify common AI use cases (e.g., computer vision, natural language processing, recommendation systems)
    • Describe the ML pipeline (e.g., data collection, training, deployment, monitoring)
    • Understand the ethics and responsible AI considerations

    13 practice questions tagged to this domain.

  4. 4

    Deployment and Operations

    20%
    • Deploy models to production using Amazon SageMaker endpoints
    • Monitor models (e.g., data drift, concept drift) using Amazon SageMaker Model Monitor
    • Manage model versions and automate CI/CD pipelines with MLOps
    • Implement scaling and cost optimization for inference

    13 practice questions tagged to this domain.

  5. 5

    Data Preparation for ML

    12%
    • Identify data types (structured, unstructured, semi-structured)
    • Apply data preprocessing techniques (e.g., cleaning, normalization, feature engineering)
    • Use AWS data services (e.g., Amazon S3, AWS Glue, Amazon Athena) for data preparation
    • Evaluate data quality and sufficiency

    8 practice questions tagged to this domain.

Three phases, in order

Most failures are process failures, not knowledge failures.

Step 1

Phase 1 — Learn the high-weight domains

Start where the points are. The first domains on this plan carry the most weight, so a gap there costs the most. Cover the objectives, then close each topic with practice questions you actually get wrong.

Step 2

Phase 2 — Close the mid-weight domains

The middle of the blueprint is where most candidates plateau. These domains are worth less per topic than the first phase, but they add up fast, and they are the usual difference between a near miss and a clear pass.

Step 3

Phase 3 — Timed full mocks

Stop reading new material at this point. Run full-length exams under the real time limit and the real format, and use the per-domain breakdown to find which domain is still costing you the pass.

Where we put the emphasis

Certilum’s AWS AI Practitioner prep uses real‑world scenario‑based practice questions covering data preparation, SageMaker, hyperparameter tuning, and model monitoring. Our practice exams mirror the official difficulty – no console needed, just diagnostic feedback and active recall.

The order matters less than the loop. Every domain you finish should end with questions you got wrong, because the mistake is the only thing you actually needed to study. On the AWS Certified AI Practitioner that loop is worth 24% of the exam in the first block alone.

More about the AWS Certified AI Practitioner exam

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