AWS Machine Learning / AI


AWS Machine Learning / AI

Authors: Mike Erickson, Raluca Bolovan, Fernando Medina Corey, Alan Jones

AWS has a number of machine learning and artificial intelligence services and products that can be used in conjunction with each other to make smart applications. In this path... Read more

What you will learn:

  • Amazon Lex
  • Amazon Comprehend
  • AWS Polly
  • Amazon Translate
  • Amazon Transcribe
  • AWS Rekognition
  • Sagemaker
  • Deep Learning on AWS


This path is for learners who possess a general knowledge of cloud computing and application development. They do not need to be experts in AI or Machine learning but will learn how to use the plug and play options on AWS in their applications.


In this section you will learn about your first artificial intelligence service that you can use in your application, Amazon Lex.

Getting Started with Amazon Lex

by Mike Erickson

Mar 13, 2018 / 1h 57m

1h 57m

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The creation of an interactive and intelligent application is helped by the use of automatic speech recognition (ASR) and natural language understanding (NLU). In Getting Started with Amazon Lex, you will be introduced to the skills required to leverage Amazon Lex to build these user interactions for the applications you create. First, you will learn how to define the intents that the ChatBot will fulfill for the user. Next, you will explore how to create the slots that will gather the required information from your user. Finally, you will discover how to implement Lambda functions that process the information gathered by your ChatBot to complete the desire of your users. When you are finished with this course, you will be prepared to create simple informational bots using Amazon Lex.

Table of contents
  1. Course Overview
  2. Introducing Lex, Amazon Lex
  3. Building Your First Amazon Lex Chatbot
  4. Improving Your Prompts
  5. Adding Fulfillment
  6. Managing Your Chatbot Lifecycle
  7. Adding Error Handling


In this section you will learn about the bulk of the options for AI on AWS for developers. Each individual course covers a machine learning or artificial intelligence service.

Building a Voice-enabled Serverless Website with AWS Polly

by Raluca Bolovan

Jul 10, 2018 / 1h 46m

1h 46m

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With the abundance of information available, it’s becoming exponentially harder to keep your users’ focus on the content you have relentlessly created. With the emergence of AWS Polly, you can breathe life into your ideas, by choosing the most evocative voice to convey your message. In this course, Building a Voice-enabled Serverless Website with AWS Polly, you’ll go through the journey of designing, building, and automating your content website, with the result of enriching your users’ experience. First, you'll explore what makes AWS Polly special and why it is the right choice for building a close interaction with your audience. Next, you'll experience the iterative process of coming up with an architecture for your website that resonates with the intent to serve your users. You'll start with the fundamentals of setting up the infrastructure for the website, ranging from local development to seeing and hearing your creation deployed on the Web. By combining concepts like Serverless computing, Infrastructure as code, CI/CD, you'll see how these new trends can be used together to save you time and make your applications resilient. Then, you'll iteratively improve the way the speech gets generated, with the help of AWS Lambda. Finally, you'll unearth new possibilities of extending and creating other voice-enabled architectures for captivating your audience. When you're finished with this course, you'll have a clear understanding of how you can use Polly to automatically narrate your content, your own functional serverless website that you can customize, and a good foundation to confidently create other applications using emerging tech methodologies.

Table of contents
  1. Course Overview
  2. Getting Started with AWS Polly
  3. Architecting and Setting Up a Speaking Website with Polly and Hugo
  4. Enhancing Your Website's Voice Capabilities
  5. Reflecting On and Extending Polly's Role in Your Site

Translating Languages on AWS with Amazon Translate

by Fernando Medina Corey

Mar 8, 2019 / 2h 32m

2h 32m

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Translating text at scale is a challenge for many organizations that want to make themselves understood internationally. In this course, Translating Languages on AWS with Amazon Translate, you will gain the ability to leverage Amazon Translate and neural machine translation in your applications. First, you will learn the basic context and benefits of neural machine translation tools. Next, you will discover how to leverage Amazon Translate APIs to scale your translation capabilities. Finally, you will explore how to integrate Amazon Translate with other AWS services such as Amazon Polly and Amazon CloudWatch. When you’re finished with this course, you will have the skills and knowledge of Amazon Translate needed to develop, secure, and monitor your own Amazon Translation applications and remove the restriction of language barriers.

Table of contents
  1. Course Overview
  2. Getting Started with Amazon Translate
  3. Translating Text in Different Formats
  4. Monitoring and Securing Amazon Translate
  5. Integrating Amazon Translate


In this section you will finish up with one last AI tool, Rekognition, and you'll also learn about the deeper side of machine learning with the powerful Sagemaker and Deep Learning Instances on AWS.

Developing Applications with AWS Rekognition

by Alan Jones

Sep 7, 2018 / 1h 27m

1h 27m

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AWS Rekognition provides powerful services for image and video processing. This course, Developing Applications with AWS Rekognition, will demonstrate how these features can be applied to your applications. First, you will cover topics like biometric access based on facial recognition and detection of unsafe content. Next, you will learn how to implement person tracking in security videos and metadata discovery for social media applications. Finally, you will see how other AWS services, like EC2 and Lambda, can work together with Rekognition to build complete applications. When you're finished with this course, you will be ready to use all of the features of Rekognition for image and video processing.

Table of contents
  1. Course Overview
  2. Introduction to Rekognition
  3. Using the Image Features of Rekognition
  4. Using the Video Features of Rekognition
  5. Building a Complete Rekognition Application
  6. Conclusion
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