100+ Free AWS Machine Learning Specialty Practice Questions
Pass your AWS Certified Machine Learning – Specialty (MLS-C01) exam on the first try — instant access, no signup required.
A data scientist needs to use word embeddings to capture semantic relationships between words (e.g., 'king' - 'man' + 'woman' = 'queen'). Which SageMaker built-in algorithm can generate these word embeddings?
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Key Facts: AWS Machine Learning Specialty Exam
65
Total Questions
AWS exam guide (50 scored + 15 unscored)
180 min
Exam Time
AWS MLS-C01 exam guide
750/1000
Passing Score
AWS scaled scoring model
$300
Exam Fee
AWS certification pricing
36%
Modeling Domain Weight
Largest domain on MLS-C01
Mar 31, 2026
Last Day to Test
AWS certification retirement notice
The AWS Machine Learning Specialty (MLS-C01) requires a scaled score of 750/1000 to pass. The exam has 65 questions (50 scored + 15 unscored) in 180 minutes. Domain 3 (Modeling) is the largest at 36%, followed by Exploratory Data Analysis (24%), Data Engineering (20%), and ML Implementation and Operations (20%). AWS recommends 2+ years of ML/deep learning experience on AWS. The exam fee is $300. Last day to test is March 31, 2026.
Sample AWS Machine Learning Specialty Practice Questions
Try these sample questions to test your AWS Machine Learning Specialty exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.
1A data engineer needs to ingest real-time clickstream data from a web application into an ML pipeline for near-real-time feature generation. Which AWS service is most appropriate for ingesting this streaming data?
2A data scientist needs to store large datasets for ML training. The data consists of structured CSV files, semi-structured JSON logs, and unstructured image files. Which storage solution provides the best foundation for an ML data lake?
3A data engineer needs to transform raw CSV files in S3 into Parquet format with schema validation before they are used for ML training. Which serverless ETL service should be used?
4A data engineer needs to orchestrate a complex ML data pipeline that includes data ingestion from multiple sources, transformation, feature engineering, and loading into a feature store. The pipeline should run on a schedule and handle dependencies between steps. Which AWS service should orchestrate this pipeline?
5A data engineer is building an ML pipeline and needs to process streaming data using Apache Spark for real-time feature computation. The solution should be fully managed and scale automatically. Which AWS service should be used?
6A data engineer needs to catalog all datasets stored across multiple S3 buckets so that data scientists can discover and understand available data for ML experiments. Which AWS service provides automated data cataloging?
7A data engineer is designing a data pipeline that processes 500 TB of historical log data for ML model training. The processing requires complex joins and aggregations using Apache Spark. Which AWS service provides the best performance for this large-scale batch processing?
8A data engineer needs to ensure that an S3 data lake supports ACID transactions for ML pipelines that perform concurrent reads and writes. Which table format should be used?
9A data engineer needs to load streaming data from Amazon Kinesis Data Streams directly into S3 in Parquet format with automatic batching and compression. Which service provides this delivery capability?
10A data engineer needs to securely share ML training datasets across multiple AWS accounts within an organization without copying the data. Which AWS service provides cross-account data sharing?
About the AWS Machine Learning Specialty Exam
The AWS Certified Machine Learning – Specialty (MLS-C01) validates expertise in building, training, tuning, and deploying ML models on AWS. The exam covers data engineering, exploratory data analysis, modeling, and ML implementation and operations. This certification is retiring March 31, 2026 — earned credentials remain active for 3 years.
Questions
65 scored questions
Time Limit
3 hours
Passing Score
750/1000
Exam Fee
$300 (Amazon Web Services (AWS))
AWS Machine Learning Specialty Exam Content Outline
Data Engineering
Data repositories, ingestion pipelines (Kinesis, Glue, EMR), data transformation, ETL processes, and storage solutions for ML workloads
Exploratory Data Analysis
Data cleaning, feature engineering, data visualization, statistical analysis, handling missing and imbalanced data
Modeling
Framing business problems as ML problems, algorithm selection, model training with SageMaker, hyperparameter tuning, and model evaluation
ML Implementation and Operations
Model deployment, inference pipelines, A/B testing, monitoring, scaling, security, and operationalizing ML solutions
How to Pass the AWS Machine Learning Specialty Exam
What You Need to Know
- Passing score: 750/1000
- Exam length: 65 questions
- Time limit: 3 hours
- Exam fee: $300
Keys to Passing
- Complete 500+ practice questions
- Score 80%+ consistently before scheduling
- Focus on highest-weighted sections
- Use our AI tutor for tough concepts
AWS Machine Learning Specialty Study Tips from Top Performers
Frequently Asked Questions
How many questions are on the AWS Machine Learning Specialty exam?
The MLS-C01 exam has 65 total questions: 50 scored items and 15 unscored pretest questions. You have 180 minutes (3 hours) to complete the exam. Questions are either multiple choice (one correct answer) or multiple response (two or more correct answers). Unscored questions are not identified during the exam.
What score do I need to pass the AWS MLS-C01 exam?
You need a minimum scaled score of 750 out of 1000 to pass. AWS uses a compensatory scoring model, meaning you do not need to pass each domain individually — your overall score determines the result. Scores are reported on a scale of 100 to 1000.
What are the four domains of the MLS-C01 exam?
The four domains are: Domain 1 — Data Engineering (20%): data ingestion, transformation, and storage; Domain 2 — Exploratory Data Analysis (24%): data cleaning, feature engineering, and visualization; Domain 3 — Modeling (36%): algorithm selection, training, hyperparameter tuning, and evaluation; Domain 4 — ML Implementation and Operations (20%): deployment, monitoring, and operationalizing ML solutions.
Is the AWS Machine Learning Specialty exam retiring?
Yes. AWS announced that the MLS-C01 exam is retiring with March 31, 2026 as the last day to test. Certification holders will still have an active certification for 3 years from the date earned. AWS recommends transitioning to the AWS Certified Machine Learning Engineer – Associate or AWS Certified AI Practitioner certifications.
How much does the AWS Machine Learning Specialty exam cost?
The MLS-C01 exam costs $300 USD. If you already hold an active AWS certification, you are eligible for a 50% discount on your next exam. Retakes also cost $300, and you must wait 14 days before retaking after a failed attempt.
How should I prepare for the AWS Machine Learning Specialty exam in 2026?
Focus on Modeling (36%) as the largest domain. Master SageMaker built-in algorithms (XGBoost, Linear Learner, DeepAR, BlazingText). Study data engineering with Glue, Kinesis, and EMR. Practice feature engineering and data preparation techniques. Understand deployment patterns including endpoints, batch transform, and inference pipelines. Complete 100+ practice questions scoring 80%+ before scheduling.