Amazon Lex -Deep Dive
Creating a Lex Bot
In this Amazon Lex course, you will be guided through an in-depth study of the Amazon Lex service. We review where and when to use this service to best effect. We'll go over Chatbots in general and why they have become both useful and popular. You will be introduced to the key features and core components within the Amazon Lex service. We spend time understanding and reviewing Amazon Lex Bots, Intents, Utterances, Slots, and Slot Types.
We focus on the developer workflow and how Amazon Lex integrates seamlessly with other AWS services. We take a look at and review the capabilities of the Amazon Lex API and associated SDKs. We review Versioning and Aliases and how they facilitate development within the Amazon Lex service. Finally, we walk you through building a fully functional chatbot implemented using the Amazon Lex service, which when completed will allow you to start and stop EC2 instances.
- Understand the basic principles of Amazon Lex for building Conversational Interfaces
- Learn how to effectively use Amazon Lex to manage and maintain your own chatbots
- Recognize and explain how to perform all basic Amazon Lex related tasks such as configuring Intents, Slots, and Lambda functions (code hooks)
- Understand IAM security permissions required for Amazon Lex to interact with other AWS services such as EC2
- Be able to competently manage Amazon Lex using the AWS console
- AWS Administrators
- Software Developers and Engineers
To be able to get the most out of this course we recommend having a basic understanding of:
- AWS Lambda
- Software Development
- Basic understanding of Python
The example code used within this course can be found here:
Related Training Content
After completing this course we recommend taking the 'Introduction to Amazon Rekognition' course.
To discover more content like this, you will find all of our training in the Cloud Academy Content Training Library.
Hello and welcome to this Cloud Academy course on Amazon Lex. Before we start, I'd like to introduce myself. My name is Jeremy Cook. I'm one of the trainers here at Cloud Academy specializing in AWS. Feel free to connect with either myself or the wider team here at Cloud Academy regarding anything about this course. You can email us at firstname.lastname@example.org. Alternatively, our online community forum is available for your feedback.
In this training course, you'll be introduced to Amazon Lex. With Amazon Lex, you can build conversational interfaces, embedding these into your new and existing applications. Your customers can then begin to engage with your applications using voice and text commands. Amazon Lex provides a simple yet powerful conversational framework and engine. Developers can leverage Amazon Lex to embed the power of chatbots directly within their applications. Amazon Lex, for example, can be used to provide chatbots that schedule meetings or that can inform you of local weather patterns and/or provide customer help desk and support channels - and that's just for starters!
The agenda for the remainder of this course is as follows. We provide a quick review of chatbots and why they've become popular in recent times. We review the complete Amazon Lex service and the machine learning technology used within. We'll provide an understanding of key components and terminology as used within Amazon Lex. We'll review suitable use cases and scenarios in which Amazon Lex can be applied effectively. We focus on the developer workflow used to build Amazon Lex chatbots. We examine how Amazon Lex integrates seamlessly with other AWS services. We take a look at and review the capabilities of the Amazon Lex API and associated SDKs. Finally, we'll walk you through building a fully functional chatbot implemented using the Amazon Lex service. The following prerequisites will be both useful and helpful for this course. Chatbots, a general understanding of chatbots.
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, GCP, Azure), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).