AWS Certified Machine Learning Specialty Practice Tests

Four Full AWS Certified Machine Learning Specialty Practice exams with Explinations (MLS-C01) | Newest questions
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*UPDATED Tests*

*This credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives. Earning AWS Certified Machine Learning – Specialty validates expertise in building, training, tuning, and deploying machine learning (ML) models on AWS.*

Practice Tests

The practice exams completely prepare you for what it is like to take in AWS Certified Machine Learning Specialty Certification Exam . These questions are collected

  • Written and answered by multiple Aws Machine learning Experts
  • Exam Questions similar to actual Certification Exam
  • Following the knowledge areas as required by the exam

There are four practice exams included and They have been designed carefully by maintaining the exam structure , syllabus, topic weights , cut score and time duration same as actual certification exam.

These practice tests are designed by our experts to simulate the real exam format. Here, you will get unlimited access to 4 practice tests with 35 unique questions in each with explinations.

All the exams will be updated and added in order to provide you with the most up-to-date content.

Lessons and Topics

The AWS Certified Machine Learning Specialty exam measures a candidate’s knowledge and skills related to the following objectives. This Practice exams will cover the features/functions below.

  • Domain 1: Data Engineering 20%
  • Domain 2: Exploratory Data Analysis 24%
  • Domain 3: Modeling 36%
  • Domain 4: Machine Learning Implementation and Operations 20%
  • TOTAL 100%

About the Exam

Read on for details about the AWS Certified Machine Learning Specialty exam.

  • Content: 65 multiple-choice
  • Time allotted to complete the exam: 180 minutes
  • Passing score: 70%
  • Exam Price: 300 (USD)

Who this course is for:

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

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