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Pattern of the Exam

MLS-C01 test contains questions in the form of multiple choice (with only one correct option) and multiple answer (more than 1 correct response). The candidates will get 180 minutes to finish the exam. Also, they need to pay $300 for registration. They can also choose preferred language from the options such as English, Simplified Chinese, Korean, and Japanese. Finally, one has the opportunity of taking the exam online or in a testing center. Topics covered include ML operations as well as implementation, exploratory data analysis, data engineering, and modeling.

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Certification Path

There is no prerequisite for AWS Certified Machine Learning Specialty exam.

Reference: https://d1.awsstatic.com/training-and-certification/docs-ml/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide%20(1).pdf

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Understanding functional and technical aspects of AWS Certified Machine Learning - Specialty Data Engineering

The following will be discussed in AMAZON MLS-C01 exam dumps:

• Identify and implement a data-ingestion solution
• Create data repositories for machine learning
• Identify and implement a data-transformation solution

Who should take the Amazon MLS exam

Candidates who have the following should take this exam:

• Design and implement scalable, cost-optimized, reliable, and secure ML solutions
• Select and justify the appropriate ML approach for a given business problem
• Identify appropriate AWS services to implement ML solutions

If a candidate wants significant improvement in career growth needs enhanced knowledge, skills, and talents. TThe AWS Certified Solutions Architect - Associate examination is intended for individuals who perform a solutions architect role and have one or more years of hands-on experience designing available, cost-efficient, fault-tolerant, and scalable distributed systems on AWS.

It asks for following experience:

• Experience performing basic hyperparameter optimization
• The ability to follow deployment and operational best practices
• 1-2 years of experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud
• Experience with ML and deep learning frameworks
• The ability to follow model-training best practices
• The ability to express the intuition behind basic ML algorithms