📋 2026 Edition · Updated November 2026

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Study Guide 2026

Q: How long does it take to prepare for the AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam?

Most candidates with relevant background take 4-8 weeks studying 1-2 hours daily. Beginners may need longer depending on their current knowledge and experience.

Q: What is included in the AWS Certified Machine Learning Engineer - Associate (MLA-C02) study guide?

The study guide covers the exam syllabus, domain-wise topics, study roadmap, preparation strategy, exam tips and links to practice, mock exams, readiness testing and other preparation resources.

Q: Is this AWS Certified Machine Learning Engineer - Associate (MLA-C02) study guide enough to pass the exam?

The study guide is designed to organize your preparation around the exam syllabus and domains. Candidates should also use practice questions and timed simulations to test their ability to apply what they have learned.

Q: Can beginners use this AWS Certified Machine Learning Engineer - Associate (MLA-C02) study guide?

Yes. The guide can be used to understand the exam domains, identify the topics to study and follow a structured preparation roadmap.

Q: How many practice questions should I do?

There is no universal number that guarantees readiness. Focus on understanding why answers are correct or incorrect and use timed practice to identify gaps in your preparation.

Q: How can I identify my weak areas?

Use the Edureify readiness diagnostic to assess your preparation and identify weaker exam domains before deciding where to spend additional study time.

Complete exam coverage for the AWS Certified Machine Learning Engineer - Associate (MLA-C02): syllabus, domains, key topics, study plan and practical exam preparation strategy.

Questions

170 min

Duration

720

Passing score

Domains

Start Practice Test & Get My Study Plan Take Readiness Diagnostic

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Overall readiness (locked)

Data Preparation for ML and AI

ML Model and Foundation Model (FM) Development

Deployment and Orchestration of ML and AI Workflows

Operating, Monitoring, and Securing ML and AI Solutions

Run 10-Minute Free Diagnostic →

Exam at a Glance

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Exam Overview

Key facts about the AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam structure, format and scoring.

🆔

aws-machine-learning-engineer-associate

Exam code

📝

85 questions

Total questions

⏱

170 minutes

Duration

🎯

720

Passing score

📋

4 domains

Exam domains

🏆

Certification

Credential type

ℹ️

Scoring method: Results are reported as a scaled score from 100 to 1,000 using a compensatory model, so only the overall score must reach the minimum; section-level feedback is informational. Unscored pretest items are not identified and do not count; unanswered questions are scored as incorrect with no penalty for guessing. The MLA-C02 exam guide sets a minimum passing score of 720 with 50 scored and 15 unscored items on the standard form; the beta form adds further unscored items (85 total), and beta results are typically released within 5 business days.. The exam may include unscored pilot questions - treat every question seriously.

Focus Areas

What should you study for the AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam?

Start with the domains that make up the AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam. Use the detailed syllabus below to work through the individual topics.

⚠️

Common mistake: Candidates often memorise terminology but struggle with scenario-based questions. Focus on when to use what, not just what exists.

🔐

Data Preparation for ML and AI (28%)

Collecting and storing data, transforming and engineering features, and validating data quality and bias.

🏗

ML Model and Foundation Model (FM) Development (24%)

Choosing modeling approaches, training and customizing models, and evaluating ML and AI system performance.

⚡

Deployment and Orchestration of ML and AI Workflows (24%)

Managing deployment infrastructure, provisioning resources and automating CI/CD for MLOps and AI workloads.

💰

Operating, Monitoring, and Securing ML and AI Solutions (24%)

Monitoring inference, optimizing infrastructure cost and performance, and securing ML and AI workloads.

Full Syllabus

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Exam Syllabus and Topics

The AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam is divided into 4 domains. Each domain covers specific skills and topics. Expand a domain to see the detailed syllabus.

Data Collection and Storage

Data sources: S3, EFS, RDS, DynamoDB and OpenSearch Service

Streaming ingestion with Kinesis, Apache Flink and Apache Kafka

Parquet, JSON, CSV and ORC formats

Vector databases with OpenSearch and RDS pgvector

SageMaker Feature Store ingestion

Transformation and Feature Engineering

AWS Glue, Glue DataBrew and SageMaker Data Wrangler

Scaling, normalization, binning and log transforms

Embedding models for text and images

Chunking and metadata for RAG

Preparing data for fine-tuning and distillation

Data Quality and Bias

Glue Data Quality validation

Data labeling and annotation

Bias metrics with SageMaker Clarify

Class imbalance handling

Outliers, missing values and deduplication

~24 questions

28 marks

28% of exam weight

Choosing Modeling Approaches

Selecting Amazon Bedrock foundation models

Custom models vs. managed AI services

RAG architecture patterns

Textract, Rekognition, Comprehend and Transcribe

Performance, latency and cost trade-offs

Training and Customization

SageMaker built-in algorithms and script mode

SageMaker automatic model tuning

Distributed training and early stopping

Overfitting, underfitting and catastrophic forgetting

Fine-tuning foundation models

Model Evaluation

MLflow on SageMaker AI experiments

Shadow variants and drift baselines

BLEU, ROUGE and BERTScore

LLM-as-a-judge and human evaluation

RAG retrieval accuracy monitoring

~21 questions

24 marks

24% of exam weight

Deployment Infrastructure

Real-time, batch and asynchronous inference

Multi-model and multi-container endpoints

Bedrock Custom Model Import

Agent deployment and communication protocols

RAG retrieval and reranking configuration

Provisioning Resources

SageMaker endpoints in a VPC

SageMaker Python SDK and Boto3

Auto scaling metrics and GPU scaling

Bedrock knowledge base management

On-demand vs. provisioned capacity

CI/CD for ML and AI

SageMaker Pipelines and CodePipeline

SageMaker Model Registry versioning

Bedrock Prompt Management

Automated retraining

Deployment rollbacks

~20 questions

24 marks

24% of exam weight

Monitoring Inference

SageMaker Model Monitor and drift detection

CloudWatch generative AI observability

A/B testing in production

Agent and tool failure monitoring

Cost and Performance Optimization

Inference instance selection

Purchasing options and Savings Plans

Token, embedding and vector storage costs

Troubleshooting with CloudWatch, X-Ray and AgentCore Observability

Securing ML and AI Workloads

Least-privilege IAM for ML artifacts

VPC isolation for ML systems

Amazon Inspector and CodeGuru scans

Bedrock API keys vs. IAM credentials

Bedrock Guardrails

CloudTrail and AWS Config auditing

~20 questions

24 marks

24% of exam weight

Study Plan

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Structured Study Roadmap

Choose a preparation timeline based on how much time you have available. For a plan based on your actual readiness and weak domains, use the personalised Edureify study experience. Get My Training Plan →

Weeks 1-2

Core Services + Highest-Weighted Domain

Deep-dive into the most heavily tested domain. Spend more time here when its exam weight is significantly higher.

Official exam guideDomain 1 completeCore conceptsPractice questions

Week 3

Domain 2 - Hands-on Practice

Focus on scenario-based study and reinforce concepts through practical application where applicable.

Domain 2Scenario walkthroughsHands-on practicePractice questions

Week 4

Domain 3 - Deeper Concepts

Work through complex concepts and decision scenarios.

Domain 3Scenario drillsPractice examReview

Week 5

Remaining Domains + Weak Area Targeting

Identify your weaker domains and spend focused time closing those gaps.

Remaining domainsDiagnosticTargeted reviewStudy notes

Week 6

Full Simulations + Final Preparation

Use timed simulations to test your preparation and review the reasoning behind incorrect answers.

Full mock examsWrong-answer reviewFinal reviewExam logistics

Exam Strategy

Tips to pass AWS Certified Machine Learning Engineer - Associate (MLA-C02) on your first attempt

Practical advice for applying what you know, managing questions and preparing for exam conditions.

🗓

MLA-C02 is in beta (English only, from September 29, 2026) at 85 questions in 170 minutes; the general availability date has not been announced.

🔍

Data Preparation for ML and AI is the largest domain at 28%; practise Glue, Data Wrangler, Feature Store and RAG data preparation.

⏭

C02 adds generative AI scope: know when to fine-tune in SageMaker AI versus customize or retrieve with Amazon Bedrock, and how to deploy agents.

📊

Deployment and orchestration (24%) rewards hands-on work with endpoints, Model Registry and SageMaker Pipelines rather than notebook-only experience.

🔁

Plan for exam stamina: at 85 questions in 170 minutes you have about 2 minutes per item.

Recommended Resources

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Study Resources

Use a focused set of resources alongside the study guide rather than trying to study from everything available.

Official

Official Exam Guide

Start with the authoritative exam objectives and blueprint.

→ Vendor website

Practice Tests

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Practice Test

Practice questions with explanations and domain-level performance analysis.

→ Start free practice test

Mock Exam

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Mock Exam

Timed preparation under realistic exam-style conditions.

→ Take free mock exam

Training

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Certification Training

Structured preparation with personalised learning support and adaptive practice.

→ AWS Certified Machine Learning Engineer - Associate (MLA-C02) certification online training

AI Tutor

AWS Certified Machine Learning Engineer - Associate (MLA-C02) AI Tutor

Get help understanding concepts and work on weak areas with AI-powered learning support.

→ Try AWS Certified Machine Learning Engineer - Associate (MLA-C02) AI tutor

Reference

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Cheat Sheet

Quick-reference summaries for final revision.

→ Get free cheat sheet

Diagnostic

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Readiness Test

Assess your preparation and identify weaker exam domains.

→ Check my readiness

⚠️

Avoid brain dumps. Sites selling real or stolen exam questions may violate certification-provider rules and can leave candidates studying outdated material.

Reviews

What candidates say after passing

FAQ

Frequently asked questions about AWS Certified Machine Learning Engineer - Associate (MLA-C02)

How long does it take to prepare for the AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam?

Most candidates with relevant background can structure their preparation over several weeks, depending on their existing knowledge, available study time and exam difficulty. Use the study roadmap above as a starting point and use the readiness diagnostic to identify where you need more preparation.

What is included in the AWS Certified Machine Learning Engineer - Associate (MLA-C02) study guide?

The guide covers the exam overview, domains, detailed syllabus and topics, study roadmap, exam preparation tips and links to practice, mock, readiness, cheat-sheet, AI Tutor and training resources.

Is this AWS Certified Machine Learning Engineer - Associate (MLA-C02) study guide enough to pass the exam?

The guide is designed to organize your preparation around the exam syllabus. You should combine it with practice questions and timed simulations so that you can test both your knowledge and your ability to apply it.

Can beginners use this AWS Certified Machine Learning Engineer - Associate (MLA-C02) study guide?

Yes. Start with the exam overview and domain breakdown, then work through the detailed topics using the study roadmap. Candidates with less experience may need additional time for foundational concepts.

How can I identify my weak areas?

Take the Edureify readiness diagnostic to assess your preparation and identify the domains where you need to focus more.

How does AI improve my preparation?

Edureify AI can help explain concepts, identify weaker areas from practice performance and support a more personalised preparation process.

Ready to prepare for AWS Certified Machine Learning Engineer - Associate (MLA-C02)?

Find your weak areas and build a more focused preparation plan.

Start My Free Diagnostic →

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AWS Certified Machine Learning Engineer - Associate (MLA-C02) Study Guide 2026

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Exam Overview

What should you study for the AWS Certified Machine Learning Engineer - Associate (MLA-C02) exam?

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Exam Syllabus and Topics

Know if you'll pass AWS Certified Machine Learning Engineer - Associate (MLA-C02) before exam day

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Structured Study Roadmap

Tips to pass AWS Certified Machine Learning Engineer - Associate (MLA-C02) on your first attempt

AWS Certified Machine Learning Engineer - Associate (MLA-C02) Study Resources

What candidates say after passing

Frequently asked questions about AWS Certified Machine Learning Engineer - Associate (MLA-C02)

Ready to prepare for AWS Certified Machine Learning Engineer - Associate (MLA-C02)?

Related Artificial Intelligence & Machine Learning Certification Study Guides