Convenience for reading and printing
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Preparation Process
Many useful resources are available for the Amazon MLS-C01 exam. Let’s take a closer look at them.
- AWS Machine Learning Documentation
The official AWS Machine Learning Documentation is one of the best preparation guides for the Amazon AWS Certified Machine Learning – Specialty exam. It is a great material to learn all the topics included in the exam content. You can find documentation, such as splitting data, data transformation, as well as types of data.
- AWS Training Courses
The vendor offers the official Amazon AWS Machine Learning Certification Training, which you can access by visiting the Amazon website. It is good to know that these training courses are usually available as free.
- Discussion Forums
Besides the official training options offered by the vendor, many websites provide the candidates with the topic details and useful information related to the exam as well as the certification. Some of these sites include Quora and ExamLabs.com.
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Advantages of AWS Certified Machine Learning Specialty Exam
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- Amazon AWS Certified Machine Learning Specialty is distinguished among competitors. AmazonAWS Certified Machine Learning Specialty can give them an edge at that time easily when candidates appear for a job interview employers seek to notify something which differentiates the individual to another.
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Reference: https://d1.awsstatic.com/training-and-certification/docs-ml/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide%20(1).pdf
No help, full refund
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Getting the Results
The minimum passing score for this test is 750 marks. The result will be reported on a scale of 100-1000. Note that there might be some unscored items in the exam that are not identified but don't affect your score. Also, always keep in mind that you don't need to succeed in each section to get a pass status and obtain the certification — only a total amount of points matters. The report is only needed to show individuals their performance in each domain and help them identify what are their weak and strong areas of Machine Learning.
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