Whizlabs

Fundamentals of AWS AI and ML Solutions

Whizlabs

Fundamentals of AWS AI and ML Solutions

Whizlabs Instructor

Instructor: Whizlabs Instructor

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the complete machine learning lifecycle, from data preparation to evaluation.

  • Learn to prepare, manage, and operationalize ML data and features using SageMaker Data Wrangler, Feature Store, and Model Monitor.

  • Identify the right AWS AI service for common business and application use cases.

Details to know

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Recently updated!

February 2026

Assessments

6 assignments

Taught in English

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There are 3 modules in this course

Welcome to Week 1 of the Fundamentals of AWS AI and ML Solutions course. In this week, you will build a strong conceptual foundation in artificial intelligence and machine learning, starting with a clear understanding of what machine learning is and how it differs from artificial intelligence and deep learning.You will explore the types of data used in machine learning systems and examine the major categories of machine learning. This week also introduces you to AWS services for machine learning, providing an overview of how managed services from Amazon Web Services support model development, training, and deployment. As part of model evaluation, you will learn how to analyze classification results using confusion matrices, interpret their outcomes, and apply evaluation metrics for both classification and regression problems. The week concludes with an introduction to deep learning, followed by a discussion on how machine learning and deep learning models are used in production environments, including key considerations such as scalability, performance, and reliability.

What's included

16 videos2 readings2 assignments

Welcome to Week 2. In this week, you will be introduced to Amazon SageMaker, AWS’s fully managed service for building, training, and deploying machine learning models at scale. You will begin with an overview of SageMaker and explore its core components through hands-on demonstrations. As the module progresses, you will take a deep dive into essential SageMaker capabilities such as Data Wrangler for data preparation, Feature Store for managing and reusing features, and Model Monitor for detecting data drift and maintaining model performance in production. By the end of this module, you will be able to confidently navigate the SageMaker ecosystem, prepare and manage ML data efficiently, operationalize features, monitor deployed models, and accelerate machine learning development using built-in templates and pretrained models.

What's included

6 videos1 reading2 assignments

Welcome to Week 3 of the Fundamentals of AWS AI and ML Solutions course. In this module, you will begin by working with language-based AI services such as Amazon Comprehend, Amazon Translate, and Amazon Transcribe, learning how to extract insights from text, translate content across languages, and convert speech into text. The module then expands into speech and vision capabilities using Amazon Polly and Amazon Rekognition, enabling you to generate lifelike speech and analyze images and videos for faces, objects, and content moderation.You will also explore conversational and search-based AI solutions with Amazon Lex and Amazon Kendra. The module also covers personalization and document intelligence through Amazon Personalize and Amazon Textract, demonstrating how AWS AI services can be used to deliver tailored user experiences and extract structured data from scanned documents.

What's included

17 videos1 reading2 assignments

Instructor

Whizlabs Instructor
Whizlabs
141 Courses 107,806 learners

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