Amazon Web Services
AWS Machine Learning Specialty
AWS Certified Machine Learning – Specialty (MLS-C01)
AWS's former specialty certification for data scientists and ML engineers who built, trained, tuned, and deployed machine learning models on AWS. RETIRED: the last day to take MLS-C01 was March 31, 2026. AWS's current ML practitioner credential is the Machine Learning Engineer – Associate (now MLA-C02). Existing MLS-C01 certifications remain active for 3 years from the date earned.
Full program: 4 decks, 968 cards.
What's on the exam
MLS-C01 Exam Guide (final version; exam retired March 31, 2026)
Data Engineering
20%Data repositories for ML (S3, lakes) · Data ingestion solutions (Kinesis, Glue) · Data transformation pipelines · Batch vs. streaming processing
Exploratory Data Analysis
24%Sanitizing and preparing data · Feature engineering · Handling missing data and outliers · Visualization and descriptive statistics · Labeling and ground truth
Modeling
36%Framing business problems as ML problems · Model selection (built-in algorithms, deep learning) · Training, tuning, and hyperparameter optimization · Evaluation metrics and validation · Overfitting, underfitting, and regularization
Machine Learning Implementation and Operations
20%Deploying and operationalizing models (SageMaker endpoints) · Performance, availability, and scaling · Security for ML solutions · Monitoring, retraining, and A/B testing · Choosing between AI services and custom models
Frequently asked questions
How much does the AWS Machine Learning Specialty cost?
The AWS Machine Learning Specialty costs $300. Final specialty-tier exam fee; exam retired March 31, 2026.
How long is the AWS Machine Learning Specialty and how many questions does it have?
65 items (50 scored, 15 unscored) — 180 minutes.
What do you need to pass the AWS Machine Learning Specialty?
Scaled score of 750 on a scale of 100–1,000.
Can you retake the AWS Machine Learning Specialty?
Not available — exam retired March 31, 2026; see AWS Certified Machine Learning Engineer – Associate.
What is the best way to study for the AWS Machine Learning Specialty?
Start from the official outline and your primary study materials: the exam is weighted by domain (Data Engineering 20%, Exploratory Data Analysis 24%, Modeling 36%, Machine Learning Implementation and Operations 20%). Once you've learned the material, spaced-repetition flashcards organized by those domains are an efficient way to retain it and refresh it before test day.
Ready to prepare?
Our AWS Machine Learning Engineer Associate program is organized by this outline's domains and scheduled by spaced repetition, with a path from first card to test day.
Flashcards are a memory tool. Learn the material first, then use NoReread to retain it and refresh what you already know. It doesn't replace studying the subject.