"AWS: Fundamentals of Machine Learning & MLOps is the first course of Exam Prep (MLA-C01): AWS Certified Machine Learning Engineer – Associate Specialization. This course assists learners in building foundational knowledge of core machine learning concepts, including types of learning, data preparation, model evaluation, and operationalization. Learners gain a strong understanding of the difference between AI, Deep Learning, and Machine Learning, and how to identify and apply real-world ML use cases using AWS services.
AWS: Machine Learning & MLOps Foundations
AWS: Machine Learning & MLOps Foundations
包含在 
中
您将学到什么
Explore the core concepts of Machine Learning and how it differs from AI and Deep Learning.
Introduce key AWS services and MLOps practices for managing the end-to-end ML lifecycle.
Explore how to build and evaluate classification and regression models using AWS ML services.
Differentiate between batch and real-time inferencing methods and identify suitable use cases for each.
您将获得的技能
- AWS SageMaker
- Applied Machine Learning
- Data Processing
- Feature Engineering
- Unsupervised Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Supervised Learning
- Data Cleansing
- Predictive Modeling
- MLOps (Machine Learning Operations)
- Amazon Web Services
- Continuous Deployment
- Machine Learning
- Regression Analysis
要了解的详细信息
可分享的证书
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最近已更新！
September 2025
作业
4 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 Exam Prep MLA-C01: AWS Machine Learning Engineer Assocaite 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有2个模块
Welcome to Week 1 of the AWS: Machine Learning & MLOps Foundations course. This week, you’ll explore the fundamentals of Machine Learning (ML) and how it differs from AI and Deep Learning. We'll cover types of data, types of ML (supervised, unsupervised, reinforcement), and how to identify suitable ML use cases. You’ll walk through the ML lifecycle—from data ingestion to deployment—and get introduced to key AWS services that support ML workflows. We’ll also touch on MLOps concepts and AWS tools that help scale and manage ML models in production.
涵盖的内容
9个视频2篇阅读材料2个作业1个讨论话题
Welcome to Week 2 of the AWS: Machine Learning & MLOps Foundations course. This week, we’ll dive into practical aspects of model building. You'll start with a classification demo, followed by learning how to select, train, and evaluate models using AWS tools. We’ll cover data preprocessing techniques, explore the confusion matrix and regression metrics, and introduce unsupervised learning through clustering. Finally, you'll understand the difference between batch and real-time inferencing, and when to apply each.
涵盖的内容
9个视频3篇阅读材料2个作业
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常见问题
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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