Learn AWS LEX with Live Project, Slack Integration and CI/CD

Create an AWS free tier account by completing the sign-up form, verifying email, setting a root password, linking a card, and validating your identity via SMS before accessing the console.

learn how aws lambda provides a serverless, on-demand backend for chatbots, with pay-per-use pricing and a generous free tier, and how to build Python functions integrated with Lex.

Create a lambda function from the hello world python blueprint, name it hello-test, deploy, test with events, and monitor logs as you prepare to integrate with Lex.

Create and configure a Lambda function using the Lex order flowers template to test Lex features, then integrate with Lex in upcoming sessions, paving the way for a live project.

Learn Amazon Lex, a fully managed AI service for building chatbots and voice assistants with advanced NLP, Slack integration, and Lambda-driven automation within a 12-month free tier.

Set up your first Amazon Lex demo bot in the v1 console, create a board, name it, select English (US), and explore sample intents and slots.

Explore how utterances drive intents in a chat bot by adding examples like hi or hello, testing responses, and binding user input to specific intents in an AWS Lex workflow.

Learn how AWS Lex slots capture user inputs as variables with prompts. See how these slot values feed the back end and lambda function in a flower order example.

Enable lambda initialization and validation in AWS Lex to process user inputs in real time, invoke lambda functions with proper permissions, and validate inputs before completing the order flow.

Explore how AWS Lex fulfillment uses a lambda to craft dynamic final messages based on user inputs, returning parameters and handling fixed or dynamic responses for order flows.

Learn to define and validate slot types in AWS Lex, including built-in Amazon date and time and custom slots, and design response cards with images and buttons.

Learn how AWS Lex handles errors in chatbots by configuring maximum retries, default responses, and custom messages to guide users through incorrect inputs.

Publish your chat bot beyond the Lex window by using supported channels like Facebook, Kik, Slack, and Twilio for web and mobile deployments.

Monitor a live chat with AWS Lex by tracking usage patterns, requests, missed utterances, and latency in the monitoring tab; use CloudWatch metrics to fine-tune your chatbot and improve performance.

Troubleshoot your AWS Lex backed chatbot by using Lambda monitor and CloudWatch logs to view log streams, verify backend execution, and track intents and errors.

Explore building an AWS Lex live project from scratch, creating intents to manage VMs and S3 buckets, hosting a static site on S3, and integrating with Slack and CI/CD pipelines.

Create an Amazon Lex bot named autopilot, set English language and voice output, enable compliance with the Child Online Privacy Protection Act, and start with a board for 5–6 intents.

Create the AWS Lex welcome intent with sample utterances like hello, configure fulfillment to return messages such as 'Welcome to Autopilot' and 'Welcome to the boat', then build and test.

Create an AWS Lex intent named instance, capture region, instance type, and ami id with slots and a confirmation prompt, then test the submission flow.

Integrate an AWS Lex intent with a Python-based Lambda function. Set up the function, enable logging, and dispatch intents to back-end processes for dynamic responses.

Learn to build an aws lex lambda workflow that captures region, instance type, and image id, creates an ec2 instance with boto3, and closes the chat with a status message.

Learn to create a stop instance intent in AWS Lex, capture the instance id via a slot, connect to a Lambda fulfillment, and test deployment to stop an EC2 instance.

Create a start instance intent in AWS Lex with an alphanumeric slot for the instance id, and implement lambda fulfillment to handle pending and running states.

Create a help intent in Lex and publish a static index.html; host on S3 with website hosting, set public access via a bucket policy, and share the URL in chat.

Integrate an AWS Lex bot with Slack by creating a Slack app, configuring interactivity and permissions, and publishing to a workspace to run commands like start, stop, and help.

Create an AWS Lex intent named bucket list, bind a lambda function to list S3 buckets, format the response, and resolve access permissions.

Set up your GitLab free account by signing up with your Gmail or Google login, enter your name, username, email, and password, accept terms, and access GitLab.

Create a new EC2 instance as a GitLab Runner, generate a key pair, launch and tag the instance as GitLab-Runner, and connect via PuTTY using the key pair.

Set up a GitLab runner on Linux, disable shared runners, install and register the runner with a project, using URL, token, tags, and a shell executor for CI/CD workflows.

Learn to configure a GitLab runner by gaining root access with sudo, renaming and managing runner files, and installing git dependencies with yum to enable builds and deployments.

Configure a GitLab CI/CD pipeline to build and deploy an AWS Lambda function. Commit a Python file, create a GitLab YAML, and zip the package for deployment.

Set up a GitLab CI pipeline to package a Lambda zip and upload it to an S3 bucket, using an IAM role with S3 and Lambda access for versioned artifacts.

Configure a GitLab deployment job to update a Lambda function using a packaged zip from an S3 bucket, specifying function name and region, with a manual approval in CI/CD.

Delete all AWS resources after the hands-on labs to avoid future charges, including buckets, instances, key pairs, chat boards, and AWS Lambda functions, then close the account in account settings.