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AWS Certified Machine Learning – Specialty Practice Exams

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Practice for the Exam with 6 practice tests for the AWS MLS certification (+400Q), explinations and references included
4.5
4.5/5
(15) Ratings
347 students
Created by Hanine El Manouzi
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What you'll learn

  • Develop a deep understanding of machine learning concepts, algorithms, and techniques.
  • Gain hands-on experience with AWS machine learning services, including Amazon SageMaker, AWS Glue, and AWS Deep Learning AMIs.
  • Master the process of data preparation, feature engineering, model training, and evaluation in AWS machine learning workflows.
  • Acquire the skills needed to design and deploy machine learning solutions on the AWS platform.
This course includes:
455 questions on-demand video
0 articles
0 downloadable resources
0 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • Familiarity with machine learning concepts and algorithms is recommended.

Description

Prepare yourself for the AWS Certified Machine Learning – Specialty certification exam with our comprehensive pack of 7 practice exams. Each practice exam consists of 65 thoughtfully curated questions designed to simulate the real exam experience. With a total duration of 170 minutes for each practice exam, you’ll have ample time to analyze complex scenarios and demonstrate your understanding of machine learning concepts.

Our practice exams cover a wide range of topics, including data preparation, feature engineering, model training, evaluation, and deployment. With detailed explanations for each question, you’ll gain insights into the reasoning behind the correct answers and strengthen your understanding of AWS machine learning services.

Course Performance:

  • 7 full-length practice exams, each containing 65 questions

  • Total duration of 170 minutes for each practice exam

  • Questions designed to mimic the format and difficulty level of the actual AWS Certified Machine Learning – Specialty exam

  • Detailed explanations provided for each question to deepen understanding

  • Opportunity to assess your performance and identify areas for improvement

  • Gain confidence and familiarity with the exam structure and question types

  • Enhance your knowledge of AWS machine learning services and best practices

Learning Objectives:

By completing this course, learners can expect to:

  • Develop a deep understanding of machine learning concepts, algorithms, and techniques.

  • Gain hands-on experience with AWS machine learning services, including Amazon SageMaker, AWS Glue, and AWS Deep Learning AMIs.

  • Master the process of data preparation, feature engineering, model training, and evaluation in AWS machine learning workflows.

  • Acquire the skills needed to design and deploy machine learning solutions on the AWS platform.

Requirements:

  • Familiarity with machine learning concepts and algorithms is recommended.

  • Basic understanding of AWS services and cloud computing.

  • Prior experience with programming languages such as Python is beneficial but not mandatory.

Who is this course for?

This course is ideal for:

  • Data scientists and machine learning engineers preparing for the AWS Certified Machine Learning – Specialty exam.

  • Professionals working with AWS machine learning services who want to validate their expertise.

  • Individuals interested in assessing their readiness for the AWS Certified Machine Learning – Specialty exam and gaining confidence in their machine learning skills.

Who this course is for:

  • Professionals working with AWS machine learning services who want to validate their expertise.
  • Individuals interested in assessing their readiness for the AWS Certified Machine Learning – Specialty exam and gaining confidence in their machine learning skills.
  • Beginners who are new to machine learning and AWS can also benefit from taking this course as a learning tool and introduction to AWS machine learning services.
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