Machine Learning Specialty Exam Guide - AWS Certified Machine Learning – Specialty (MLS-C01)

Sep 20, 2026

Uploaded by Terk

AWS Certified Machine Learning – Specialty (MLS-C01) is an assessment for candidates performing AI/ML development or data science on AWS. The exam measures the ability to design, build, deploy, optimize, train, tune, and maintain machine learning solutions using AWS Cloud services. It evaluates selecting a suitable ML approach, choosing appropriate AWS services, and implementing scalable, cost-optimized, reliable, and secure ML systems. Target experience includes 2+ years with AWS-based ML or deep learning workloads, plus familiarity with frameworks and best practices.

LanguageEnglish

CategoryExam

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Introduction

Target candidate description

Recommended AWS knowledge

Out of scope for the target candidate

Exam content

Response types

Unscored content

Exam results

Content outline

Domain 1: Data Engineering

Domain 2: Exploratory Data Analysis

Domain 3: Modeling

Domain 4: Machine Learning Implementation and Operations

Introduction The AWS Certified Machine Learning – Specialty (MLS-C01) exam is intended for individuals who perform an artificial intelligence/machine learning (AI/ML) development or data science role. The exam validates a candidate’s ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for given business problems by using the AWS Cloud. The exam also validates a candidate’s ability to complete the following tasks: 􀁸 Select and justify the appropriate ML approach for a given business problem 􀁸 Identify appropriate AWS services to implement ML solutions 􀁸 Design and implement scalable, cost-optimized, reliable, and secure ML solutions Target candidate description The target candidate is expected to have 2 or more years of hands-on experience developing, architecting, and running ML or deep learning workloads in the AWS Cloud. Recommended AWS knowledge The target candidate should have the following knowledge: 􀁸 The ability to express the intuition behind basic ML algorithms 􀁸 Experience performing basic hyperparameter optimization 􀁸 Experience with ML and deep learning frameworks 􀁸 The ability to follow model-training best practices 􀁸 The ability to follow deployment best practices 􀁸 The ability to follow operational best practices What is considered out of scope for the target candidate? The following is a non-exhaustive list of related job tasks that the target candidate is not expected to be able to perform. These items are considered out of scope for the exam: 􀁸 Extensive or complex algorithm development 􀁸 Extensive hyperparameter optimization 􀁸 Complex mathematical proofs and computations 􀁸 Advanced networking and network design 􀁸 Advanced database, security, and DevOps concepts 􀁸 DevOps-related tasks for Amazon EMR For a detailed list of specific tools and technologies that might be covered on the exam, as well as lists of in-scope and out-of-scope AWS services, refer to the Appendix. Exam content Response types There are two types of questions on the exam: 􀁸 Multiple choice: Has one correct response and three incorrect responses (distractors) 􀁸 Multiple response: Has two or more correct responses out of five or more response options Select one or more responses that best complete the statement or answer the question. Distractors, or incorrect answers, are response options that a candidate with incomplete knowledge or skill might choose. Distractors are generally plausible responses that match the content area. Unanswered questions are scored as incorrect; there is no penalty for guessing. The exam includes 50 questions that will affect your score. Unscored content The exam includes 15 unscored questions that do not affect your score. AWS collects information about candidate performance on these unscored questions to evaluate these questions for future use as scored questions. These unscored questions are not identified on the exam. Exam results The AWS Certified Machine Learning – Specialty (MLS-C01) exam is a pass or fail exam. The exam is scored against a minimum standard established by AWS professionals who follow certification industry best practices and guidelines. Your results for the exam are reported as a scaled score of 100–1,000. The minimum passing score is 750. Your score shows how you performed on the exam as a whole and whether or not you passed. Scaled scoring models help equate scores across multiple exam forms that might have slightly different difficulty levels. Your score report could contain a table of classifications of your performance at each section level. This information is intended to provide general feedback about your exam performance. The exam uses a compensatory scoring model, which means that you do not need to achieve a passing score in each section. You need to pass only the overall exam. Each section of the exam has a specific weighting, so some sections have more questions than oth

FAQs

What skills does the AWS MLS-C01 exam validate for candidates?

It validates the ability to design, build, deploy, optimize, train, tune, and maintain ML solutions using AWS Cloud, including selecting an ML approach, choosing AWS services, and implementing scalable, cost-optimized, reliable, and secure systems.

What experience and AWS knowledge are expected from the target candidate?

Candidates are expected to have 2 or more years of hands-on experience developing, architecting, and running ML or deep learning workloads in AWS, plus familiarity with ML algorithms intuition, basic hyperparameter optimization, ML/deep learning frameworks, and best practices for training, deployment, and operations.

How is the exam scored and what do results look like?

The exam is pass or fail, scored against AWS-established minimum standards. Scores are reported as a scaled score from 100 to 1,000, with a minimum passing score of 750, and results may include section-level classification tables with compensatory scoring.

Sep 20, 2026

Uploaded by Terk