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AWS: Machine Learning & MLOps Foundations

本课程是 Exam Prep MLA-C01: AWS Machine Learning Engineer Associate 专项课程的一部分

位教师：Whizlabs Instructor

1,559 人已注册

包含在中

了解更多

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

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

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

4 项作业

授课语言：英语（English）

91% of learners achieved a positive career outcome

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积累特定领域的专业知识

本课程是 Exam Prep MLA-C01: AWS Machine Learning Engineer Associate 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

"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.

This course allows learners to explore key topics such as model selection, classification workflows, confusion matrices, and regression evaluation techniques. In addition, learners are introduced to the concepts of MLOps and the AWS services used to streamline ML deployment and monitoring in production environments. The course is divided into two modules, and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:30–3:00 hours of video lectures that provide both theory and hands-on knowledge using AWS tools. Also, Graded and Ungraded Quizzes are provided with every module to test the understanding and application readiness of learners." Module 1: Machine Learning and MLOps Concepts Module 2 : Model Development & Evaluation Techniques By the end of this course, learners will be able to: - Apply foundational machine learning and MLOps concepts using AWS tools - Build and evaluate ML models with services like Amazon SageMaker - Understand end-to-end ML workflows, including data preparation, model training, and deployment - Strengthen their preparation for the AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam This course is ideal for aspiring ML practitioners, data engineers, and developers with 6 months to 1 year of AWS experience who want to build practical skills in machine learning and MLOps. It also supports learners preparing for the AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam and professionals seeking hands-on knowledge of implementing and managing ML workflows using AWS services.

单元详情

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

10个视频2篇阅读材料2个作业

10个视频总计55分钟

Welcome to Specialization5分钟
What is Machine Learning?5分钟
Understanding difference - AI Vs Deep Learning Vs Machine Learning3分钟
Types of Data8分钟
Types of Machine Learning5分钟
Identify the Machine Learing Use Case8分钟
Steps for Machine Learning7分钟
AWS Services for Machine Learning6分钟
What is MLOps ?5分钟
AWS Services for MLOps4分钟

2篇阅读材料总计45分钟

Welcome to the Course30分钟
Overview of Machine Learning Concepts & Use Cases15分钟

2个作业总计45分钟

Foundations of Machine Learning & Use Cases - Knowledge Check25分钟
Machine Learning Concepts & Use Cases [Machine Learning and MLOps Concepts & Use Cases] - Assessment20分钟

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.