Practice Exams AWS Machine Learning Speciality Tests 2024

The AWS Certified Machine Learning - Specialty (MLS-C01) exam is intended for individuals who perform an artificial intelligence/machine learning (AI/ML) development or data science role. The exam validates a candidate’s ability to design, build, deploy, optimize, train, tune, and maintain ML solutions for given business problems by using the AWS Cloud. The exam also validates a candidate’s ability to complete the following tasks:

 Select and justify the appropriate ML approach for a given business problem.

 Identify appropriate AWS services to implement ML solutions.

 Design and implement scalable, cost-optimized, reliable, and secure ML solutions

The exam has the following content domains and weightings:

 Domain 1: Data Engineering (20% of scored content)

 Domain 2: Exploratory Data Analysis (24% of scored content)

 Domain 3: Modeling (36% of scored content)

 Domain 4: Machine Learning Implementation and Operations (20% of scored content)

Sample Questions:

1) A machine learning team has several large CSV datasets in Amazon S3. Historically, models built with the Amazon SageMaker Linear Learner algorithm have taken hours to train on similar-sized datasets. The team’s leaders need to accelerate the training process. What can a machine learning specialist do to address this concern?

A) Use Amazon SageMaker Pipe mode.

B) Use Amazon Machine Learning to train the models.

C) Use Amazon Kinesis to stream the data to Amazon SageMaker.

D) Use AWS Glue to transform the CSV dataset to the JSON format.

2) A term frequency–inverse document frequency (tf–idf) matrix using both unigrams and bigrams is built from a text corpus consisting of the following two sentences:

1. Please call the number below.

2. Please do not call us.

What are the dimensions of the tf–idf matrix?

A) (2, 16)

B) (2, 8)

C) (2, 10)

D) (8, 10)

3) A company is setting up a system to manage all of the datasets it stores in Amazon S3. The company would like to automate running transformation jobs on the data and maintaining a catalog of the metadata concerning the datasets. The solution should require the least amount of setup and maintenance. Which solution will allow the company to achieve its goals?

A) Create an Amazon EMR cluster with Apache Hive installed. Then, create a Hive metastore and a script to run transformation jobs on a schedule.

B) Create an AWS Glue crawler to populate the AWS Glue Data Catalog. Then, author an AWS Glue ETL job, and set up a schedule for data transformation jobs.

C) Create an Amazon EMR cluster with Apache Spark installed. Then, create an Apache Hive metastore and a script to run transformation jobs on a schedule.

D) Create an Amazon SageMaker Jupyter notebook instance that transforms the data. Then, create an Apache Hive metastore and a script to run transformation jobs on a schedule.

4) A data scientist is working on optimizing a model during the training process by varying multiple parameters. The data scientist observes that, during multiple runs with identical parameters, the loss function converges to different, yet stable, values. What should the data scientist do to improve the training process?

A) Increase the learning rate. Keep the batch size the same.

B) Decrease the learning rate. Reduce the batch size.

C) Decrease the learning rate. Keep the batch size the same.

D) Do not change the learning rate. Increase the batch size.

5) A data scientist is evaluating different binary classification models. A false positive result is 5 times more expensive (from a business perspective) than a false negative result. The models should be evaluated based on the following criteria:

1) Must have a recall rate of at least 80%

2) Must have a false positive rate of 10% or less

3) Must minimize business costs After creating each binary classification model, the data scientist generates the corresponding confusion matrix. Which confusion matrix represents the model that satisfies the requirements?

A) TN = 91, FP = 9 FN = 22, TP = 78

B) TN = 99, FP = 1 FN = 21, TP = 79

C) TN = 96, FP = 4 FN = 10, TP = 90

D) TN = 98, FP = 2 FN = 18, TP = 82

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