AWS Certified Machine Learning – Specialty
This AWS specialty certification validates the ability to build, train, tune, and deploy machine learning models on the AWS cloud platform.
What Is This Certification?
The exam covers data engineering, exploratory data analysis, ML modeling, and ML implementation and operations on AWS services like SageMaker. It targets data scientists and ML engineers working in the AWS ecosystem.
Eligibility & Requirements
recommended 1–2 years of ML experience on AWS; aimed at data scientists and ML engineers.
Exam Format & Structure
65 questions (multiple choice and multiple response), 180 minutes, Pearson VUE or online proctored.
Cost & Fees
$300 USD.
Validity & Renewal
Valid 3 years; recertify by passing the current version of the exam.
Salary & Career Outlook
AWS ML specialists commonly earn $130,000–$170,000+, among the highest cloud-cert salaries.
Compare AWS Certified Machine Learning – Specialty
See how this certification stacks up against others:
Top Training Providers & Resources
- AWS Skill Builder
- A Cloud Guru
- Udemy (Stephane Maarek)
- Coursera
Is AWS Certified Machine Learning – Specialty Worth It?
This cert is worth it if you build ML systems on AWS or want to move into cloud ML engineering — it is one of the highest-paying specialty credentials and signals deep, current AWS ML skill. It is less worth it for beginners with no ML foundation or teams not on AWS. The value: it proves you can take models from data prep through deployment on SageMaker and production AWS services, which is exactly what employers hiring ML engineers need. Paired with a solutions-architect cert, it makes for a very strong cloud-ML profile and commands premium compensation.
How to Prepare
Prep in 2–4 months. 1) Solidify ML fundamentals: algorithms, evaluation metrics, feature engineering. 2) Learn SageMaker deeply — training, tuning, deployment, and built-in algorithms. 3) Study the four domains, especially data engineering and ML ops. 4) Use Stephane Maarek's or A Cloud Guru's course plus AWS Skill Builder labs. 5) Take practice exams and review AWS whitepapers on ML best practices. 6) Get hands-on in the AWS console — the exam rewards practical service knowledge over theory alone.
How to Get AWS Certified Machine Learning – Specialty Certified
- Confirm you meet the requirements: recommended 1–2 years of ML experience on AWS; aimed at data scientists and ML engineers.
- Download the official exam blueprint / handbook from Amazon Web Services and map it to a study plan.
- Choose prep that fits you — official materials, a course, and/or a bootcamp — and set a weekly schedule.
- Study the core topics and practice until the skills are automatic.
- Take full-length practice exams and target a steady pass-rate before booking. Exam format: 65 questions (multiple choice and multiple response), 180 minutes, Pearson VUE or online proctored.
- Book the exam ($300 USD.) at a test center or online proctor, then sit and pass it.
- Receive your credential from Amazon Web Services and add it to your resume, LinkedIn, and this profile.
- Track renewal: Valid 3 years; recertify by passing the current version of the exam. — log continuing education early.
Career Paths & Job Titles
- Machine Learning Engineer
- Data Scientist
- MLOps Engineer
- AI Solutions Architect
- Cloud Data Engineer
Skills You'll Gain
- Reading the exam blueprint / objectives
- Hands-on with the core platform or toolset
- Troubleshooting and best-practice execution
- Compliance and quality fundamentals
- Documenting and explaining professional decisions
Who Should Get This Certification?
career changers, students, and working pros who want a recognized, resume-ready credential
Good fit if…
- You want a credentialed, resume-ready proof of skill in this field.
- The AWS Certified Machine Learning – Specialty is required or preferred for the roles you're targeting.
- You learn well from structured study + practice and can commit the prep time.
Maybe skip if…
- You need deep, multi-year expertise — this is a foundational/mid credential, not a replacement for experience.
- The topic isn't relevant to your actual career goal.
- You can't meet the eligibility or renewal requirements — check those with the provider first.
Frequently Asked Questions
What is the AWS Certified Machine Learning – Specialty and who is it for?
AWS Certified Machine Learning – Specialty is offered by Amazon Web Services. The exam covers data engineering, exploratory data analysis, ML modeling, and ML implementation and operations on AWS services like SageMaker. It targets data scientists and ML engineers working in the AWS ecosystem. It is aimed at recommended 1–2 years of ML experience on AWS; aimed at data scientists and ML engineers.
How much does the AWS Certified Machine Learning – Specialty exam cost?
The exam costs $300 USD. Budget for potential retakes and any exam-prep materials you choose separately.
How long is the AWS Certified Machine Learning – Specialty valid, and how do I renew it?
Valid 3 years; recertify by passing the current version of the exam. Renewal requirements vary, so confirm the current policy with Amazon Web Services before your renewal date.
What does the AWS Certified Machine Learning – Specialty exam format look like?
The exam is structured as follows: 65 questions (multiple choice and multiple response), 180 minutes, Pearson VUE or online proctored. Knowing the format in advance lets you pace yourself and practice the question types you'll face.
Am I eligible for the AWS Certified Machine Learning – Specialty?
Eligibility: recommended 1–2 years of ML experience on AWS; aimed at data scientists and ML engineers. Review the official handbook from Amazon Web Services because eligibility rules and documentation can change.
How long should I study for the AWS Certified Machine Learning – Specialty?
Most candidates prepare over a focused window that depends on background and the exam's depth. Use the official exam blueprint from Amazon Web Services, pair it with a reputable prep course, and take full-length practice exams until you're consistently above the pass threshold.
What is the salary outlook after earning the AWS Certified Machine Learning – Specialty?
AWS ML specialists commonly earn $130,000–$170,000+, among the highest cloud-cert salaries. Salaries also depend on region, experience, and related credentials, so treat this as a directional range rather than a guarantee.
Is the AWS Certified Machine Learning – Specialty worth it for my career?
That depends on your goals. This cert is worth it if you build ML systems on AWS or want to move into cloud ML engineering — it is one of the highest-paying specialty credentials and signals deep, current AWS ML skill. It is less worth it for beginners with no ML foundation or teams not on AWS. The value: it proves you can take models from data prep through deployment on SageMaker and production AWS services, which is exactly what employers hiring ML engineers need. Paired with a solutions-architect cert, it makes for a very strong cloud-ML profile and commands premium compensation.
Do I need hands-on experience before taking the AWS Certified Machine Learning – Specialty?
Hands-on practice strongly improves pass rates even when not strictly required. Follow the exam objectives from Amazon Web Services and build real familiarity before test day.
Which comes after the AWS Certified Machine Learning – Specialty?
After this credential, candidates typically pursue the next-level or a complementary cert. Check Amazon Web Services's certification path to sequence credentials efficiently.
Can I take the AWS Certified Machine Learning – Specialty exam online?
Many providers offer both testing-center and online-proctored options. Online proctoring has strict environment rules (clean desk, ID, stable connection), so verify requirements with Amazon Web Services before booking.