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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.

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2026 Statistics

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.

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

20%

Data Engineering

Data repositories, ingestion pipelines (Kinesis, Glue, EMR), data transformation, ETL processes, and storage solutions for ML workloads

24%

Exploratory Data Analysis

Data cleaning, feature engineering, data visualization, statistical analysis, handling missing and imbalanced data

36%

Modeling

Framing business problems as ML problems, algorithm selection, model training with SageMaker, hyperparameter tuning, and model evaluation

20%

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

1Focus on Modeling (36%) — master SageMaker built-in algorithms, training jobs, hyperparameter tuning, and model evaluation metrics
2Know when to use each SageMaker algorithm: XGBoost for tabular data, Linear Learner for regression/classification, DeepAR for time series, BlazingText for NLP
3Study Exploratory Data Analysis deeply (24%): feature engineering, handling missing data, normalization, PCA, and data visualization
4Understand data engineering pipelines: Kinesis for streaming, Glue for ETL, EMR for large-scale processing, S3 for storage
5Master deployment patterns: real-time endpoints, batch transform, multi-model endpoints, and A/B testing with production variants
6Review ML operations: model monitoring with Model Monitor, retraining triggers, and pipeline automation with SageMaker Pipelines
7Practice with timed 65-question sessions to build pacing discipline for the 3-hour exam

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.