AWS Certified Machine Learning Engineer – Associate (MLA-C02)
Updated ML Engineer – Associate exam. Registration opens September 2026; domains to be confirmed from the published exam guide.
What's on the exam
4 domains · 12 task statements, straight from the official exam guide (as of 2026-09-16).
- 1.1Collect and store data
- Skill 1.1.1: Extract data from data sources (for example, Amazon S3, Amazon EBS, Amazon EFS, Amazon RDS, Amazon DynamoDB, Amazon OpenSearch Service).
- Skill 1.1.2: Make storage decisions and configure storage services based on cost, performance, data structure, and data compliance.
- Skill 1.1.3: Troubleshoot and debug data ingestion and storage issues that involve capacity and scalability.
- Skill 1.1.4: Use AWS streaming data sources to ingest data (for example, by using Amazon Kinesis, Apache Flink, Apache Kafka).
- Skill 1.1.5: Ingest from and write by using appropriate data formats (for example, Apache Parquet, JSON, CSV, ORC) based on data access patterns.
- Skill 1.1.6: Merge data from multiple sources (for example, by using programming techniques, AWS Glue, Apache Spark).
- Skill 1.1.7: Configure scalable vector databases for AI applications (for example, OpenSearch Service, Amazon RDS with pgvector, Amazon S3) based on specifications.
- Skill 1.1.8: Ingest and store diverse data types (for example, text, images, audio) for AI and ML applications.
- 1.2Perform data transformation, feature engineering, and preprocessing
- Skill 1.2.1: Transform data by using AWS tools (for example, AWS Glue, AWS Glue DataBrew, Spark on Amazon EMR, SageMaker Data Wrangler).
- Skill 1.2.2: Create and manage features by using AWS tools (for example, SageMaker Feature Store).
- Skill 1.2.3: Transform streaming data (for example, by using AWS Lambda, Spark).
- Skill 1.2.4: Perform feature engineering (for example, scaling, standardization, feature splitting, binning, log transformation, normalization).
- Skill 1.2.5: Configure and use embedding models to transform text and image data into numerical representations.
- Skill 1.2.6: Apply advanced text pre-processing techniques (for example, tokenization, domainspecific augmentation).
- Skill 1.2.7: Prepare documents for Retrieval Augmented Generation (RAG) applications (for example, chunking strategies, metadata extraction).
- Skill 1.2.8: Mask, redact, and anonymize data.
- Skill 1.2.9: Prepare data for FM fine-tuning, continuous pre-training, and model distillation. AWS Certified Machine Learning Engineer - Associate
- 1.3Validate data quality and manage bias
- Skill 1.3.1: Validate data quality (for example, by using DataBrew, AWS Glue Data Quality).
- Skill 1.3.2: Label and annotate data.
- Skill 1.3.3: Identify and mitigate sources of bias in data by using AWS tools and techniques (for example, dataset splitting, shuffling, augmentation).
- Skill 1.3.4: Optimize multimodal data distributions by applying bias metrics across numeric, text, and image assets.
- Skill 1.3.5: Resolve class imbalance in numeric, text, and image datasets.
- Skill 1.3.6: Validate AI training data integrity (for example, prompt-response pair validation, content safety screening).
- Skill 1.3.7: Clean data (for example, by detecting outliers, imputing missing data, deduplication).
Outline reproduced from the vendor's public exam guide for study reference.Official guide
MLA-C02 practice — frequently asked questions
Are these real MLA-C02 exam questions?
No. Every question on CertifyCloudx is original, written by us against Amazon Web Services's publicly available MLA-C02 exam guide to rehearse the skills it lists. None are actual exam questions, and CertifyCloudx is not affiliated with or endorsed by Amazon Web Services.
How many MLA-C02 practice questions are there?
0 practice questions. Every question has a detailed explanation of why the right answer wins and why each distractor loses.
Is the content up to date with the current MLA-C02 exam guide?
The questions are written against the MLA-C02 exam guide dated 2026-09-16, and we revise them when Amazon Web Services updates the guide.
What question formats are covered?
The same formats the real MLA-C02 uses: Multiple choice, Multiple response, Ordering, Matching, case study. Each is rendered and graded the way the exam does it.
How long is the MLA-C02 exam and how many questions does it have?
According to Amazon Web Services's published exam details: 65 questions, 130 minutes, passing score 720 / 1000. Our mock exams use the same time limit and question count. Always confirm current details with Amazon Web Services before booking.
Can I practise MLA-C02 for free?
Yes. with up to 10 questions a day on the free plan and no card needed. Pro unlocks every paper and mock exam with no daily limit.
Does CertifyCloudx guarantee that I will pass?
No practice material can guarantee a result. CertifyCloudx helps you find and close your weak areas — accuracy by exam-guide domain and topic shows what to study next.