[Scenario: Deploy Simple Web Application in Lambda. Tags: Lambda, API Gateway]

[Scenario: Learn to deploy application on Amazon ECS Fargate. Tags: Fargate, ECS, ECR, Docker]

[Scenario: Learn to deploy application on Amazon ECS. Tags: ECS, ECR, Docker]

[Scenario: Learn to manage EC2 instances in Private Subnet using AWS Systems Manager. Tags: Systems Manager, Private Subnet, EC2]

[Scenario: Learn create, query, update and delete operations with Elasticsearch. Tags: Elasticsearch]

[Scenario: Configure PostgreSQL Database as data source for Amazon Athena. Tags: Amazon Athena, RDS PostgreSQL, Federated Query]

[Scenario: Process data in Amazon EMR Cluster using AWS Glue Catalog. Tags: Amazon EMR, AWS Glue, PySpark]

[Scenario: Using Amazon Comprehend Custom Classification to identity real / fake news title. Tags: Amazon Comprehend, Custom Classification, Amazon SageMaker]

[Scenario: Learn to use AWS Data Wrangler with Amazon Redshift. Tags: Redshift, Data Wrangler, Pandas]

[Scenario: Configure a Lambda Function which uses container as the runtime. Tags: Lambda, Container, Docker, ECR]

[Scenario: Configure Federated Query between Redshift and PostgreSQL Databases. Tags: Redshift, PostgreSQL, Federated Query]

[Scenario: Configure and use private API in API Gateway. Tags: VPC, API Gateway, Endpoint, Python, Lambda]

[Scenario: Use AWS IoT Analytics with AWS IoT Core and analyze data using Jypyter Notebook. Tags: IoT Core, IoT Analytics, Jupyter Notebook]

[Scenario: Introductory workshop to learn about fundamentals of Amazon EMR. Tags: Amazon EMR]

[Scenario: Use Glue Studio to create Glue Job which performs ETL from AWS RDS Database to Amazon S3 Bucket. Tags: AWS Glue Studio, RDS, S3]

[Scenario: Use DataBrew to transform RDS data and convert the transformation into an automated job. Tags: AWS Glue DataBrew, RDS, S3]

[Scenario: Using Amazon Lake Formation Blueprint to create data import pipeline. Tags: AWS Lake Formation, AWS Glue, RDS, S3]

[Scenario: Create data lake using AWS Lake Formation and AWS Glue where the data is stored in Amazon Redshift Database. Tags: AWS Glue, S3, , Redshift, Lake Formation]

[Scenario: Using AWS Glue Workflow to orchestrate crawler and job execution. AWS Services: S3, AWS Glue]

[Scenario: Learn how to use jobs to update the devices using AWS IoT Device Management. AWS Services: AWS IoT Core, AWS IoT Device Management, Cloud9, Python, S3]

[Scenario: Using AWS IoT Core to publish device messages to the AWS Lambda Function. AWS Services: AWS IoT Core, AWS Lambda]

[Scenario: Using AWS Glue Job and AWS Glue Network Connection to call APIs. Tags: AWS Glue, S3, Python, REST API]

[Scenario: Use custom labels in Amazon Rekognition to identity custom objects in the pictures. AWS Services: Amazon Rekognition, AWS Cloud9, S3]

[Scenario: Using Amazon Personalize to build model to provide recommendations. AWS Services: Amazon Personalize, AWS Cloud9, S3]

[Scenario: Use code based custom transformation in AWS Glue Job using AWS Glue Studio. AWS Services: AWS Glue, AWS Lake Formation, Amazon S3, PySpark, Scala]

[Scenario: Using AWS IoT Core to publish device messages in to Amazon Timestream. AWS Services: AWS IoT Core, Amazon Timestream]

[Scenario: Create AWS Glue Job using AWS Glue Studio. AWS Services: AWS Glue, AWS Lake Formation, Amazon S3]

[Scenario: Create AppSync API with Lambada function and call using Python based client. AWS Services: AWS AppSync, AWS Lambada, AWS Cloud9, Amazon DynamoDB]

[Scenario: Build Model using Amazon Forecast and call as an API. AWS Services: Amazon Forecast, Cloud9, S3]

[Scenario: Use AWS IoT Device Defender Security Profile to detect anomaly. AWS Services: AWS IoT Core, AWS IoT Device Defender, Amazon SNS]

[Scenario: Train Fraud Detection Model and use as an API to predict fraud. AWS Services: Amazon Fraud Detector]

[Scenario: Build Application using Amazon Cloud Map based service discovery. AWS Services: Amazon Cloud Map]

[Scenario: Using Amazon Comprehend to analyze the text. AWS Services: Comprehend]

[Scenario: Using Glue Catalog Table Schema to transform data format in Kinesis Delivery Stream. AWS Services: Kinesis Data Stream, Kinesis Delivery Stream, Glue Catalog Table]

[Scenario: Python programming with Amazon Transcribe to covert voice into text. AWS Services: Transcribe, Python Boto3 SDK]

[Scenario: Python programming with Amazon Lex to create a chat bot. AWS Services: Lex, Python Boto3 SDK]

[Scenario: Python programming with Polly, Translate & Textract for text to voice conversion, language translation and document scanning. AWS Services: Polly, Translate, Textract, Python Boto3 SDK]

[Scenario: Learn message exchange between IoT device and AWS IoT Core using Python Code. AWS Services: AWS IoT Core, Python, AWS IoT Device SDK]

[Scenario: Using PySpark to create AWS Glue Job. Tags: AWS Glue, PySpark]

[Scenario: Using PySpark to create AWS Glue Job. Tags: AWS Glue, PySpark]

[Scenario: Create Glue Job to process streaming data. Tags: AWS Glue, Kinesis, IoT, S3]

[Scenario: Learn working of device shadow service in AWS IoT Core. Tags: Amazon IoT Core, Shadow]

[Scenario: Create search service with Amazon Kendra using S3 and Salesforce as the data sources. Tags: Amazon Kendra, S3, Salesforce]

[Scenario: Create self-service repository to allow users to create AWS resources in standard and controlled way. Tags: Amazon Service Catalog, CloudFormation]

[Scenario: Create data lake using AWS Lake Formation and AWS Glue where the data is stored in Amazon S3. Tags: AWS Glue, S3, Lake Formation]

[Scenario: Using Glue Job to copy data from the REST API to Amazon S3 Bucket. Tags: AWS Glue, S3, Python, REST API]

[Scenario: Learn message exchange between IoT device and AWS IoT Core. AWS Services: AWS IoT Core, S3, Kinesis]