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AWS ML Engineer AssociatePractice With A Network Lab Atmosphere

验证您在 AWS 上构建、训练、部署和维护机器学习解决方案的实际工程能力。涵盖 SageMaker 全生命周期管理。

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65 questions in the bankMock ExamAI Explanation助理级🤖 AI/ML
Bank size
65
Live total in the bank — no vague estimates
Mock pace
170min
65-question timed simulation
Outcomes
78%
Pass-rate data, updated continuously
540usersPass rate78%Updated regularlyDetailed explanation per question

AWS ML Engineer Associate Exam Bank

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Certification Overview

AWS Certified Machine Learning Engineer - Associate (MLA-C01)

AWS Certified Machine Learning Engineer - Associate (MLA-C01) 是 AWS 于 2024 年推出的机器学习工程认证，验证您使用 AWS 服务构建、部署和运维 ML 解决方案的能力。

Who Is This For

  • 机器学习工程师
  • 数据工程师（ML 方向）
  • MLOps 工程师
  • 使用 AWS 构建 ML 解决方案的全栈工程师

Prerequisites

  • 了解基本的机器学习概念（监督/无监督学习、模型评估）
  • 有 Python 编程经验
  • 了解 AWS 核心服务（S3、IAM、Lambda）
  • 有数据处理和 ETL 经验
  • 建议有 1 年以上 ML 或数据工程相关经验

Learning Outcomes

  • 获得 AWS 官方认可的 Machine Learning Engineer Associate 认证
  • 掌握 SageMaker 全生命周期 ML 解决方案开发
  • 精通 ML 数据准备、特征工程和模型训练
  • 具备 ML 模型部署、监控和运维能力
  • 提升 ML 工程师岗位竞争力

Exam Prep Highlights

6 个系统化学习章节，覆盖考试 4 大领域
49+ 精选练习题，每题附详细解析
仿真模拟考试（65 题/170 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 MLA-C01 最新考纲

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SAMPLE0 / 3 answered
Q 1 / 3Deployment and Orchestration

A company needs a central model registry to manage different versions of models in a SageMaker application. Which action meets this requirement with the LEAST operational overhead?

This is a preview of 3 questions. Unlock 46+ more with full detailed explanations.

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Exam Overview

Exam Domains

Data Preparation for ML
数据准备
28%
Model Development
模型开发
26%
Deployment and Orchestration
部署与编排
22%
Monitoring and Security
监控与安全
24%

Exam Information

Exam Code
MLA-C01
Duration
170 min
Questions
65
Passing Score
720/1000
Exam Fee
$150
Validity
3 years
Question Types
Single choice, Multiple select
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