1. You are building a machine learning application that requires you to train a model and make predictions based on the input data. You have decided to use AWS Lambda to run your machine learning application. However, you are concerned about the cost of running your Lambda function. Which of the following options would be the best way to reduce the cost of running your Lambda function?

A) Use the AWS Step Functions to orchestrate your Lambda function.
B) Use the serverless framework to manage your Lambda function.
C) Increase the memory allocation of your Lambda function.
D) Reduce the timeout limit of your Lambda function.



2. Which of the following statements accurately describe the features of Amazon S3 Select for machine learning workflows?

A) Amazon S3 Select supports querying of unstructured data such as images, videos, and audio files for machine learning purposes.
B) Amazon S3 Select enables filtering and processing of data directly in S3 without the need to transfer the entire dataset to a compute instance.
C) Amazon S3 Select provides automatic data compression for all data stored in S3, reducing storage costs for machine learning workloads.
D) Amazon S3 Select provides pre-built machine learning algorithms and models for common use cases such as image classification and natural language processing.
E) Amazon S3 Select provides automatic data indexing for all data stored in S3, improving query performance for machine learning workloads.


3. You are working on an AWS Machine Learning project where you need to collect and ingest data from various sources. Which of the following services can be used for collecting and processing data from social media platforms?(Select 2answers)

A) AWS Kinesis Data Streams
B) Amazon Pinpoint
C) Amazon Kinesis Video Streams
D) Amazon S3
E) AWS Glue


4. A company wants to use Amazon QuickSight to visualize and analyze their sales data, which is stored in an Amazon RDS database. They want to use a custom SQL query to aggregate the data and display it on a dashboard. Which of the following options describes the best way to achieve this?

A) Use the built-in connectors in QuickSight to connect to RDS and create a dashboard. Use the custom SQL query to aggregate the data and create a custom metric. Use this metric to visualize the data in QuickSight.
B) Use AWS Lambda to process the data in RDS, transform it, and load it into Amazon Redshift. Connect QuickSight to Redshift and create the dashboard. Use Spectrum to query the data and generate the custom metrics.
C) Use Amazon Kinesis Data Firehose to transform and load the data into Amazon Elasticsearch. Connect QuickSight to Elasticsearch and create the dashboard. Use Kibana to query the data and generate the custom metrics.
D) Use AWS Glue to crawl and catalog the data in RDS, and then create a Glue ETL job to transform and load the data into Amazon S3. Connect QuickSight to S3 and create the dashboard. Use Athena to query the data and generate the custom metrics.



5. Which of the following statements is true about AWS Lambda and its resource allocation?

A) Lambda automatically allocates CPU power, network bandwidth, and memory based on the function's configuration.
B) The developer can allocate a fixed amount of CPU power and memory to their Lambda function, and network bandwidth is automatically adjusted based on the function's traffic.
C) The developer can allocate a fixed amount of network bandwidth and memory to their Lambda function, and CPU power is automatically adjusted based on the function's traffic.
D) AWS Lambda does not provide any control over CPU power, network bandwidth, or memory allocation.
E) Lambda automatically scales CPU power, network bandwidth, and memory allocation based on the function's usage, and the developer has no control over the resources.