Applied AI · Expert tier
AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026)
AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) is a expert-tier Applied AI credential from Amazon Web Services. The exam runs $300 and covers data engineering for ml: feature engineering, data preparation, and pipeline design. Most candidates prepare for around 150 hours and pair the credential with a portfolio of platform-aligned work.
Related free ISC2 CC practice: 60 questions, right or wrong on every answer.Practice ISC2 CC free
Exam fee
$300
Prep time
150h
Duration
180 min
Level
Expert
Where this credential sits
AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) sits at the expert tier. The credential targets practitioners with multi-year platform depth who are consolidating senior or staff-track recognition.
Practice this exam
Practice the ISC2 Certified in Cybersecurity (CC) exam
AI systems still need the security basics. ISC2 CC covers them: threats, access control, secure design and operations.
- 60 practice questions in the bank.
- Practice and timed mocks are free, with right or wrong on every answer and your total score.
- Full analysis: $39, one payment for this exam, no subscription. 30-day full refund, no questions asked.
Start free ISC2 CC practiceNot sure which exam? Take Match
ISC2 Certified in Cybersecurity (CC) is a trademark of ISC2. DecipherU is not affiliated with or endorsed by ISC2.
One ISC2 CC practice question Security Operations
A new analyst is configuring system hardening on a database server. Which combination of steps best matches the ISC2 CC hardening framework?
Pick an answer. We tell you right or wrong.
Planning a ISC2 CC exam date? See which version you are taking, with the owner dates and the day we read each one.
What this certification covers
- Data engineering for ML: feature engineering, data preparation, and pipeline design
- Exploratory data analysis and modeling approaches across classical and deep learning
- ML model deployment, monitoring, and lifecycle management on AWS
- ML implementation across SageMaker, AWS Glue, EMR, Kinesis, and adjacent services
- Security, cost, and performance considerations for production ML workloads
- Operationalization, including model versioning, A/B testing, and shadow deployment
Who should pursue this
- ML engineers consolidating production AWS ML experience into a senior credential
- Data scientists moving into engineering roles on AWS infrastructure
- Solutions architects with an ML-heavy customer portfolio
Prerequisites
- No formal prerequisites
- AWS recommends 1-2 years of hands-on experience developing, architecting, or running ML workloads on AWS
- Strong Python plus SQL fluency and working knowledge of classical ML and deep learning
- This exam can no longer be scheduled. For new candidates: AWS Certified Machine Learning Engineer Associate covers SageMaker-centric MLOps closest to MLS-C01's scope, AWS Certified AI Practitioner covers foundation-level AI/GenAI, and AWS Certified Generative AI Developer Professional covers building on Bedrock and foundation models
Cost breakdown
Exam
$300
Training
Free to $2000
Recertification
Every 3y
Total first-year cost runs from $300 (exam-only with free self-study) up to $2300 with paid instructor-led training. Recertification every 3 years.
Pricing reflects publicly listed vendor pricing as of April 2026. Verify current pricing at the Amazon Web Services certification page before registering.
Difficulty assessment
Study hours
150h
Exam format
Multiple choice and multiple response. MLS-C01 was retired March 31
Passing score
Approximate 750/1000 scaled score
Heavy preparation load at roughly 150 hours of focused study. Most candidates with active cloud and ML engineering background prepare across 8 to 14 weeks. Candidates without prior platform experience should expect closer to 16 weeks. Pass rates are not officially published by Amazon Web Services, so plan against the study-hour estimate rather than guessing at exam difficulty from forum threads.
Full exam format: Multiple choice and multiple response. MLS-C01 was retired March 31, 2026 and can no longer be scheduled; AWS split its scope across three newer credentials rather than a single 1:1 replacement, because MLS-C01's blueprint had no Bedrock or generative-AI content and AWS judged that gap too large to patch. Existing holders keep their certification for its normal 3-year validity.. Total seat time: 180 minutes.
Roles this credential supports
Alternatives and adjacent credentials
- AWS Certified Machine Learning Engineer Associate (direct successor for SageMaker/MLOps scope; MLA-C01 is the current live exam through September 28, 2026, with MLA-C02's exam guide published but still in beta and no GA date announced)
- AWS Certified AI Practitioner (foundation-level successor for AI/GenAI scope)
- AWS Certified Generative AI Developer Professional (successor for Bedrock/foundation-model scope)
- Google Cloud Professional Machine Learning Engineer (vendor-equivalent for GCP-centric teams)
- Azure AI Engineer Associate (Microsoft equivalent for Azure-centric teams; also mid-transition to AI-103)
AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) questions and answers
What is the AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026)?
AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) is a expert-tier Applied AI credential from Amazon Web Services. The exam runs $300 and covers data engineering for ml: feature engineering, data preparation, and pipeline design. Most candidates prepare for around 150 hours.
How much does the AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) cost?
The exam itself is $300 as of April 2026. Training adds Free to $2000, with free self-study options available for most cloud-platform credentials. Recertification every 3 years. Verify current pricing at the Amazon Web Services website before registering.
Who should pursue the AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026)?
ML engineers consolidating production AWS ML experience into a senior credential. Data scientists moving into engineering roles on AWS infrastructure The credential is most useful when paired with a real portfolio of work on the platform.
How does the AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) compare to alternatives?
Practitioners typically choose between AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) and AWS Certified Machine Learning Engineer Associate (direct successor for SageMaker/MLOps scope; MLA-C01 is the current live exam through September 28, 2026, with MLA-C02's exam guide published but still in beta and no GA date announced) or AWS Certified AI Practitioner (foundation-level successor for AI/GenAI scope). Pick the credential matched to your target employer's primary cloud or governance stack. Studying for one credential builds 60 to 70 percent of the conceptual ground for the others.
Is the AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) worth it for a job search?
Practitioner-tier credentials carry hiring weight when the resume is otherwise platform-aligned. The AWS Certified Machine Learning - Specialty (MLS-C01, retired March 31, 2026) validates that the candidate has worked at production depth on Amazon Web Services tooling, not read about it.
Practice this exam
- AWS Certified Machine Learning - SpecialtyMLS-C01 can no longer be scheduled. This content stays for holders studying for renewal or comparison; new candidates should look at AWS ML Engineer Associate, AI Practitioner, or Generative AI Developer Professional instead.
Methodology
This guide reflects DecipherU's standard certification intelligence workflow grounded in official certifying body documentation, publicly listed exam pricing, and independent practitioner sourcing. All details verified against the Amazon Web Services certification page on 2026-09-26.
Certification details are sourced from official certifying body websites. Verify current pricing, exam format, and requirements directly with the certifying organization before making decisions. DecipherU is not affiliated with any certifying body.