Understand and Apply AI Fundamentals with AWS

本课程是 Apply AI Foundations with Python and AWS 专项课程的一部分

位教师：EDUCBA

访问权限由 New York State Department of Labor 提供

6个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

6个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Explain core AI, machine learning, and deep learning concepts and how AI systems work.
Analyze AI applications such as NLP, computer vision, generative AI, and ethical AI practices.
Evaluate and apply AWS AI services to design real-world, scalable AI solutions.

您将获得的技能

AWS SageMaker
Machine Learning
Deep Learning
Convolutional Neural Networks
Amazon Web Services
Applied Machine Learning
Model Deployment
Ethical Standards And Conduct
Natural Language Processing
Responsible AI
Unsupervised Learning
Artificial Intelligence and Machine Learning (AI/ML)
Artificial Intelligence
Supervised Learning
Reinforcement Learning
技能部分已折叠。显示 8 项技能，共 15 项。

要了解的详细信息

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作业

24 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

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Apply AI Foundations with Python and AWS 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。

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获得对主题或工具的基础理解
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获得可共享的职业证书

该课程共有6个模块

By the end of this course, learners will be able to explain core artificial intelligence concepts, analyze machine learning approaches, apply deep learning principles, and evaluate AI solutions using AWS services.

This comprehensive course is designed to build strong foundations in AI fundamentals and core concepts, progressing from classical AI techniques and machine learning to deep learning, generative models, and real-world AI applications. Learners will gain a clear understanding of how AI systems reason, learn, and make decisions, supported by practical insights into NLP, computer vision, reinforcement learning, and ethical AI practices. What makes this course unique is its balanced blend of theory, practice, and cloud-based implementation. It not only explains how AI works, but also how AI is applied at scale using AWS AI services such as SageMaker, Lex, Polly, Rekognition, and foundation models. Structured modules, lesson-wise objectives, practice quizzes, and graded assessments ensure progressive mastery and exam readiness. This course is ideal for beginners, aspiring AI practitioners, and professionals preparing for the AWS Certified AI Practitioner exam, enabling learners to confidently apply AI concepts to real-world business and industry use cases.

This module introduces the fundamental concepts of Artificial Intelligence, including its history, importance, ethical considerations, and the logical and statistical foundations that support intelligent systems.

涵盖的内容

7个视频4个作业

7个视频总计42分钟

Definition and Brief History of AI Part 1 8分钟
Definition and Brief History of AI Part 2 8分钟
Importance and Applications of AI 3分钟
AI Ethics and Societal Impacts 10分钟
Introduction 2分钟
Logic and Reasoning 7分钟
Probability and Statistics 5分钟

4个作业总计60分钟

Graded-Foundations of Artificial Intelligence 30分钟
Understanding Artificial Intelligence 10分钟
AI in Society 10分钟
Core Reasoning Foundations 10分钟

This module explores classical AI techniques such as search algorithms, knowledge representation, and foundational machine learning approaches, focusing on how machines solve problems and identify patterns.

涵盖的内容

6个视频4个作业

6个视频总计33分钟

Search Algorithms 3分钟
Knowledge Representation and Reasoning 5分钟
Introduction to Machine Learning AI 4分钟
Supervised Learning 6分钟
Unsupervised Learning 6分钟
Clustering 9分钟

4个作业总计60分钟

Graded-Classical AI and Problem-Solving 30分钟
Search and Knowledge Representation 10分钟
Machine Learning Overview 10分钟
Unsupervised Learning Fundamentals 10分钟

This module provides an in-depth understanding of core machine learning techniques, including similarity measures, dimensionality reduction, pattern discovery, and reinforcement learning methods.

涵盖的内容

8个视频4个作业

8个视频总计70分钟

Distance Measures 5分钟
Dimensionality Reductio Part 1 6分钟
Dimensionality Reductio Part 2 8分钟
Association Rule Learning 12分钟
Reinforcement Learning 11分钟
Types of Reinforcement Learning Part 1 13分钟
Types of Reinforcement Learning Part 2.1 6分钟
Types of Reinforcement Learning Part 2.2 9分钟

4个作业总计60分钟

Graded-Machine Learning Techniques 30分钟
Data Similarity and Reduction 10分钟
Pattern Discovery 10分钟
Reinforcement Learning Types 10分钟

This module introduces deep learning concepts, neural network architectures, and advanced AI paradigms such as generative models and transfer learning used in modern AI applications.

涵盖的内容

11个视频4个作业

11个视频总计84分钟

Neural Networks Basics Part 1 6分钟
Neural Networks Basics Part 2 9分钟
Deep Learning Introduction 8分钟
Convolutional Neural Networks (CNNs) Part 1 6分钟
Convolutional Neural Networks (CNNs) Part 2 8分钟
Recurrent Neural Networks (RNN) Part 1 6分钟
Recurrent Neural Networks (RNN) Part 2 7分钟
Recurrent Neural Networks (RNN) Part 3 7分钟
Generative Models Part 1 7分钟
Generative Models Part 2 12分钟
Transfer Learning and Fine Tuning 9分钟

4个作业总计60分钟

Graded-Deep Learning and Advanced AI 30分钟
Neural Network Foundations 10分钟
Specialized Neural Architectures 10分钟
Modern Learning Paradigms 10分钟

This module focuses on practical AI applications across industries and introduces AWS AI services, enabling learners to understand how AI solutions are deployed at scale.

涵盖的内容

8个视频4个作业

8个视频总计12分钟

Introduction to AWS Certified AI Practitioner 0分钟
Understanding AI and ML 3分钟
Natural Language Processing (NLP) 1分钟
Computer Vison (CV) 2分钟
Applications of AI in Various Industries 2分钟
Supervised vs Unsupervised Machine Learning 1分钟
Algorithms of Supervised and Unsupervised Machine Learning 2分钟
Reinforcement Learning (RL) 1分钟

4个作业总计60分钟

Graded-AI Applications and AWS AI Services 30分钟
AI in Practice 10分钟
AI Domains and Industry Use 10分钟
Machine Learning Comparisons 10分钟

This module covers the end-to-end AI lifecycle, including model building, deployment, ethical best practices, AWS implementation, prompt engineering, and exam readiness.