Understand and Apply AI Fundamentals with AWS

This course is part of Apply AI Foundations with Python and AWS Specialization

Instructor: EDUCBA

Access provided by ExxonMobil

6 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

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.

Skills you'll gain

Applied Machine Learning
Machine Learning
Natural Language Processing
Ethical Standards And Conduct
Model Deployment
Reinforcement Learning
Amazon Web Services
AWS SageMaker
Supervised Learning
Artificial Intelligence
Artificial Intelligence and Machine Learning (AI/ML)
Deep Learning
Unsupervised Learning
Convolutional Neural Networks
Responsible AI
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Details to know

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Assessments

24 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Apply AI Foundations with Python and AWS Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 6 modules in this course

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.

What's included

7 videos4 assignments

7 videos Total 42 minutes

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

4 assignments Total 60 minutes

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

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.

What's included

6 videos4 assignments

6 videos Total 33 minutes

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

4 assignments Total 60 minutes

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

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

What's included

8 videos4 assignments

8 videos Total 70 minutes

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

4 assignments Total 60 minutes

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

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.

What's included

11 videos4 assignments

11 videos Total 84 minutes

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

4 assignments Total 60 minutes

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

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.

What's included

8 videos4 assignments

8 videos Total 12 minutes

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

4 assignments Total 60 minutes

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

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