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  4. AWS
  5. MLS-C01
AWS专家级AI/ML

AWS Certified Machine Learning - Specialty (MLS-C01)

验证您在 AWS 平台上设计、实施和维护机器学习解决方案的专家级能力。涵盖数据工程、EDA、建模和 ML 运维。

Try the first chapter freePractice questions
65
Official exam questions
180 min
Exam duration
750/1000
Passing score
JR ACADEMY / CERTIFICATION PREP

JR Academy practice bank

453practice questions
Build your foundation6 learning chapters
Practice with purposeFocused practice · answer explanations
Test your readinessMock exams · review

453 practice questions available

OverviewExam scopeLearning pathFAQReviews
01

Understand the certification

认证概述

AWS Certified Machine Learning - Specialty (MLS-C01) 是 AWS 面向具有丰富 ML 经验的数据科学家和 ML 工程师提供的专家级认证,验证您在 AWS 上设计、构建、训练、调优和部署 ML 模型的全面能力。

考试领域

  • Data Engineering(数据工程)— 20%
  • Exploratory Data Analysis(探索性数据分析)— 24%
  • Modeling(建模)— 36%
  • Machine Learning Implementation and Operations(ML 实施与运维)— 20%

适合人群

  • 数据科学家和高级 ML 工程师
  • 有 2 年以上 ML 实践经验的技术专家
  • 希望验证 AWS ML 专家能力的技术负责人
  • AI/ML 解决方案架构师

Exam at a glance

Exam code
MLS-C01
Provider
AWS
Format
Single choice / Multiple select
Language
English / 日本語 / 한국어 / 简体中文
Validity
3 years
Exam fee
$300
Official certification page

Skills in focus

SageMakerS3KinesisGlueFeature EngineeringXGBoostDeep LearningModel TuningA/B TestingEMRAthenaComprehendRekognitionLex

Learning outcomes

  • 获得 AWS 官方认可的 Machine Learning Specialty 认证
  • 掌握端到端 ML 解决方案的设计与实施
  • 精通数据工程、特征工程和模型优化
  • 具备选择和调优 ML 算法的专家能力
  • 提升数据科学家和 ML 架构师岗位竞争力

Who this is for

  • 有 2 年以上 ML 开发和数据分析经验的数据科学家
  • 希望获得 AWS ML 专家认证的高级 ML 工程师
  • AI/ML 解决方案架构师
  • 希望转型 ML 方向的高级软件工程师
  • 数据科学和人工智能专业的研究生

Before you start

  • 1-2 年 AWS 云服务使用经验
  • 2 年以上机器学习/深度学习实践经验
  • 熟练掌握 Python 和 ML 框架(TensorFlow/PyTorch)
  • 扎实的统计学和线性代数基础
  • 了解数据工程和 ETL 流程
02

What the exam tests

20%

Data Engineering

KinesisGlueEMR数据管道S3 数据湖数据格式转换
24%

Exploratory Data Analysis

数据可视化特征选择数据清洗统计分析降维数据分布分析
36%

Modeling

SageMaker 内置算法深度学习超参数调优模型评估正则化集成学习
20%

ML Implementation and Operations

模型部署A/B 测试SageMaker Neo边缘推理CI/CD模型监控

What do you still need before the AWS ML Specialty exam?

Tell us what you do now and where you want to go. See your gaps in skills, evidence, experience, expression and positioning, and what to work on first. No sign-in needed.

Compare with my situation
03

Your learning path

6 chapters

01MLS-C01 考试概述与备考指南Free02数据工程Free03探索性数据分析140 min04建模180 min05ML 实施与运维120 min06考前冲刺与实战演练60 min
View the full learning path

Plan your preparation

Learning hours
70h
With relevant experience
6-8 weeks
Starting from scratch
10-14 weeks
Daily study
1-2h

Included in your preparation

  • 6 个系统化学习章节,覆盖考试 4 大领域
  • 453 精选练习题,每题附详细解析
  • 仿真模拟考试(65 题/180 分钟)
  • 错题本 + 智能复习,薄弱环节针对性突破
  • 学习进度可视化追踪
  • 同步 AWS 官方 MLS-C01 最新考纲

Preparation tips

  • 65 题 180 分钟,平均每题 3 分钟,合理分配时间
  • 及格分 750/1000,不确定的题先标记跳过,回头再做
  • 排除法非常有用 — 先排掉明显错误的选项,剩下的再分析
  • 多选题会告诉你选几个,仔细看题目要求

Common mistakes

  • 没有读完所有选项就选答案 — 题目经常有"最佳"答案和"正确但不最佳"的干扰项
  • 备考只刷题不理解原理 — 考试场景题需要理解底层概念
  • 忽略时间管理 — 在难题上卡太久,导致后面简单题没时间做
04

Before you register

Will the MLS-C01 exam continue to be available?

AWS has introduced the new MLA-C01 (Associate) certification, but MLS-C01 (Specialty) is still active. AWS typically provides advance notice of certification retirement plans. MLS-C01 focuses on ML theory and algorithm depth, positioning it differently from MLA-C01.

How hard is the MLS-C01 exam?

MLS-C01 is a Specialty-level certification with high difficulty. The exam covers ML theory (such as bias-variance tradeoff, regularization, algorithm selection) and AWS service practices. At least 2 years of ML experience is recommended, and a solid foundation in statistics is required. The passing score is 750/1000.

What ML algorithms do I need to know for MLS-C01?

You need to understand supervised learning (linear regression, logistic regression, SVM, decision trees, XGBoost, random forests), unsupervised learning (K-Means, PCA, t-SNE), deep learning (CNN, RNN/LSTM), and recommendation systems (collaborative filtering) — their use cases and pros/cons.

What is the MLS-C01 exam fee?

The MLS-C01 exam costs $300 USD. If you already hold an AWS certification, you can use a 50% discount voucher, bringing the actual cost to $150. The exam is 180 minutes with 65 questions.

Do I need to study deep learning for MLS-C01?

Yes, the MLS-C01 exam includes deep learning content such as CNN (image classification), RNN/LSTM (time series prediction, NLP), and transfer learning. However, you don't need paper-level depth — understanding architecture principles, use cases, and SageMaker built-in algorithm usage is sufficient.

05

Learner experiences

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06

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Done reading? Next steps

What do you still need before the AWS ML Specialty exam?

Tell us what you do now and where you want to go. See your gaps in skills, evidence, experience, expression and positioning, and what to work on first. No sign-in needed.

Compare with my situation
  • SkillPractise AWS ML Specialty by exam domainQuestions are grouped by the official exam domains, so you can see which domain still needs work.Open the question bank →
  • SkillAWS ML Specialty learning pathWork through the exam scope chapter by chapter, then come back to the questions.See the learning path →

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2 free chapters · Full preparation from $39

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