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Amazon - AWS Certified Machine Learning - Specialty (MLS-C01) Certification
Exam Guide, Study Materials & Practice Questions 2026

Last Updated on Apr 3, 2026

Amazon AWS Certified Machine Learning - Specialty (MLS-C01) certification exam guide is your essential resource for mastering the skills needed to design and deploy machine learning solutions on AWS. This certification validates your expertise and significantly boosts your career development in the growing field of AI and cloud computing. With comprehensive study materials and targeted practice questions, you’ll gain the foundational knowledge and hands-on experience required to confidently tackle the exam. To clear the exam, focus on understanding AWS ML services deeply and practicing real-world scenarios. Start your exam preparation today and take a major step toward advancing your professional journey. — Tharun Kumar and John Ellis, Technology Consultants @nxtexam

FAQ

Frequently Asked Questions

Find answers to common questions about AWS Certified Machine Learning - Specialty (MLS-C01) Certification. If you need additional help, our support team is always here to assist you with your certification journey.

What is the AWS Certified Machine Learning - Specialty (MLS-C01) certification?

The AWS Certified Machine Learning - Specialty (MLS-C01) certification validates your expertise in building, training, and deploying machine learning models on AWS. It is designed for professionals who have experience working with machine learning and AWS services.

Who should take the AWS Certified Machine Learning - Specialty certification?

This certification is ideal for machine learning practitioners, data scientists, and developers who want to demonstrate their skills in machine learning on the AWS platform. It is suitable for individuals who have experience in machine learning and AWS services.

What are the prerequisites for the AWS Certified Machine Learning - Specialty certification?

While there are no formal prerequisites, it is recommended to have at least one to two years of experience with machine learning, data science, and using AWS services like SageMaker, EC2, and S3 before attempting the MLS-C01 exam.

How can I prepare for the AWS Certified Machine Learning - Specialty exam?

To prepare for the exam, you can take AWS training courses, review the exam guide, practice with sample questions, and gain hands-on experience with AWS machine learning services such as Amazon SageMaker. AWS also offers a whitepaper and exam readiness resources.

What topics are covered in the AWS Certified Machine Learning - Specialty exam?

The exam covers a variety of topics, including data engineering, exploratory data analysis, modeling, machine learning implementation, and operationalization using AWS machine learning tools and services like Amazon SageMaker, Lambda, and S3.

How much does the AWS Certified Machine Learning - Specialty exam cost?

The cost of the AWS Certified Machine Learning - Specialty exam is $300 USD. Prices may vary depending on your region, and you can check the official AWS certification page for any updates or discounts.

How long is the AWS Certified Machine Learning - Specialty exam?

The AWS Certified Machine Learning - Specialty exam lasts for 180 minutes (3 hours). You will need to answer 65 multiple-choice and multiple-response questions.

What is the passing score for the AWS Certified Machine Learning - Specialty exam?

The passing score for the AWS Certified Machine Learning - Specialty exam is 750 out of a possible 1000 points. It is recommended to thoroughly prepare and practice before attempting the exam.

How often can I retake the AWS Certified Machine Learning - Specialty exam?

If you do not pass the exam, you can retake it after 14 days. AWS has a policy that allows candidates to retake the exam up to three times per year.

What are the benefits of earning the AWS Certified Machine Learning - Specialty certification?

Earning the AWS Certified Machine Learning - Specialty certification demonstrates your expertise in machine learning and AWS services, which can lead to career advancement opportunities, recognition within your organization, and a higher earning potential.

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