• Exam Breakdown
  • Domain Breakdown
  • Access Breakdown

Exam Format

  •  Exam Code: MLS-C01
  •  Certification Level: Specialty
  •  Exam Duration: 180 minutes
  •  Passing Score: 750 out of 1000 (scaled score)
  •  Unscored Content: The exam may include unscored questions for research purposes. These do not affect your score and are not identified.

Exam Details

  •  Question Types: Multiple choice, multiple response
  •  Number of Questions: 65 questions
  •  Hands-On Questions: No hands-on labs; exam evaluates practical and scenario-based knowledge of machine learning solutions on AWS.

Exam Policies

  •  Offline Proctoring: Must be rescheduled or canceled at least 24 hours before the scheduled exam time.
  •  Online Proctoring: Must be rescheduled or canceled at least 24 hours before the scheduled exam time.
  •  Waiting Period: A minimum 14-day wait is required after a failed attempt before retaking the exam.
  •  Retake Fee: Full exam fee must be paid for each retake.

Certification Validity and Renewal

  •  Validity: 3 years
  •  Renewal Options: Recertify by passing the latest version of the exam or through AWS recertification options.

Exam Fee

  •  Base Fee: $300 USD (excluding taxes)
  •  Taxes: Country-specific VAT may apply
    . Example: In India, 18% tax applies, making the total $354 USD ($300 + $54 tax)

Prerequisites

There are no formal prerequisites for taking the AWS Certified Machine Learning – Specialty exam. However, AWS recommends:
  •  1–2 years of hands-on experience developing, running, and maintaining ML or deep learning workloads on AWS
  •  Experience with data engineering, model training, tuning, and deployment
  •  Understanding of ML algorithms, hyperparameter optimization, and performance metrics
  •  Knowledge of AWS ML services such as Amazon SageMaker.

Exam Topics

  •  Data Engineering: Data ingestion, transformation, and feature engineering
  •  Exploratory Data Analysis: Data preparation and visualization techniques
  •  Modeling: Model selection, training, evaluation, and tuning
  •  Machine Learning Implementation and Operations: Deployment, monitoring, and optimization of ML solutions

Intended Audience

The AWS Certified Machine Learning – Specialty certification is ideal for professionals working in AI and machine learning roles, including:
  •  Machine Learning Engineer
  •  Data Scientist
  •  AI Engineer
  •  Cloud ML Developer
  •  Data Engineer working with ML workloads

Career Impact

  •  Jobs You Can Get: Machine Learning Engineer, Data Scientist, AI Engineer, ML Solutions Architect, Cloud ML Specialist, etc.
    Average Salary: Varies by country — U.S.: $110,000–$160,000 USD, India: ₹10,00,000–₹30,00,000 INR, United Kingdom: £60,000–£100,000 GBP, UAE: 200,000–400,000 AED per year.
  •  Why It’s Valuable: Demonstrates advanced machine learning expertise on AWS and validates the ability to deploy production-ready ML solutions in cloud environments.

Exam Mode

The exam is proctored and can be taken:
  • At authorized Pearson VUE test centers
  • Online proctored through Pearson VUE’s platform

Exam Booking Link

  • Available through the AWS Certification Portal under “Machine Learning – Specialty (MLS‑C01)”
 

After Passing

  • Certificate and digital badge issued via your AWS Certification Account—typically available within hours to a few days after passing.
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    Top Reasons to Choose
    AWS Certified Machine Learning – Specialty

    High Demand for Machine Learning Skills

    Organizations increasingly rely on AI and machine learning to drive data-driven decisions and automation, creating strong demand for ML professionals.

    Strong Focus on Real-World ML Implementation

    The certification emphasizes real-world ML lifecycle skills including data preparation, model training, deployment, and optimization.

    Career Growth and Global Recognition

    As an AWS Specialty-level certification, it validates advanced AI and ML expertise and enhances career opportunities in cloud and data science roles.

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