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
Skills in focus
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
What the exam tests
20%Data Engineering
Data Engineering
24%Exploratory Data Analysis
Exploratory Data Analysis
36%Modeling
Modeling
20%ML Implementation and Operations
ML Implementation and Operations
Your learning path
6 chapters
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
- 456 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
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.
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