This credential helps organizations identify and develop talent with critical skills for implementing cloud initiatives. Earning AWS Certified Machine Learning – Specialty validates expertise in building, training, tuning, and deploying machine learning (ML) models on AWS.
Who should take this exam?
AWS Certified Machine Learning - Specialty is intended for individuals who perform a development or data science role and have more than one year of experience developing, architecting, or running machine learning/deep learning workloads in the AWS Cloud. Before you take this exam, we recommend you have:
- At least two years of hands-on experience developing, architecting, and running ML or deep learning workloads in the AWS Cloud
- Ability to express the intuition behind basic ML algorithms
- Experience performing basic hyperparameter optimization
- Experience with ML and deep learning frameworks
- Ability to follow model-training, deployment, and operational best practices
Prerequisites
To earn this certification, you’ll need to take and pass the AWS Certified Machine Learning – Specialty exam (MLS-C01). The exam features a combination of two question formats: multiple choice and multiple response. Additional information, such as the exam content outline and passing score, is in the exam guide.
Recommended training for this certification
Data Scientist
- The Elements of Data Science (elearning)
- Data Science Capstone: Real World ML Decisions (elearning)
- Machine Learning Data Readiness (elearning)
- Developing Machine Learning Applications (elearning)
- Practical Data Science with Amazon SageMaker (PDSASM)
- Machine Learning Pipeline on AWS (ML-PIPE)
- Machine Learning Security (elearning)
- Exam Readiness: AWS Certified Machine Learning - Specialty (ERMLS)
- Deep Learning on AWS (AWSDL)
Developer
- ML Building Blocks: Services and Terminology (elearning)
- Process Model: CRISP-DM on the AWS Stack (elearning)
- The Elements of Data Science (elearning)
- Developing Machine Learning Applications (elearning)
- Practical Data Science with Amazon SageMaker (PDSASM)
- Machine Learning Pipeline on AWS (ML-PIPE)
- Machine Learning Security (elearning)
- Exam Readiness: AWS Certified Machine Learning - Specialty (ERMLS)
- Deep Learning on AWS (AWSDL)
Optional:
- Math for Machine Learning (elearning)
- Linear and Logistic Regression (elearning)
- Speaking Of : Machine Translation and NLP (elearning)
- Seeing Clearly: Computer Vision Theory (elearning)
Exams
AWS Certified Machine Learning – Specialty exam (MLS-C01)
Recertification
AWS Certifications are valid for three years. To maintain your AWS Certified status, we require you to periodically demonstrate your continued expertise though a process called recertification. Recertification helps strengthen the overall value of your AWS Certification and shows individuals and employers that your credential covers the latest AWS knowledge, skills, and best practices.
Recertification for the Specialty certification
Take the Current Specialty exam
You can take the current Specialty exam for the certification you already have. For example, if you are an AWS Certified Security – Specialist, you can retake the current AWS Certified Security – Specialty exam to recertify. You can use your 50% discount voucher from the Benefits section of your AWS Certification account to recertify or apply it to any future certification exam you wish to pursue.