Amazon Web Services (AWS)
Data & AI · Expert
Eligibility for AWS Certified Machine Learning – Specialty is set by Amazon Web Services (AWS), not by Koshish, and it changes between policy versions — check the issuer's current requirements for the criteria that apply to your attempt. This page covers what happens on Koshish once you are eligible to sit the exam.
Summarised from Amazon Web Services (AWS)'s published requirements rather than copied wholesale, so this page cannot drift out of date silently.
AWS recommends preparation through the developer and data-analytics associate or professional exams; these are recommendations rather than enforced prerequisites.
Recertification follows AWS's published cycle for the credential.
The Data & AI practice loop, once this certification's bank exists.
Subject- and topic-filtered practice across the Data & AI domains the certification covers
A daily plan that blends new practice with FSRS spaced revision of what you have already attempted
Per-topic ability estimates (IRT theta and BKT mastery) that surface your weakest domains first
A rationale on every attempt, reactive to the specific mistake you made rather than a generic explanation
Weak-topic analysis that decides what comes next instead of leaving the order to you
Worth knowing before you plan your preparation timeline.
No verified AWS ML Specialty question bank exists yet, so no practice sessions or mock exams are published for this certification. The syllabus and exam information above are published now; the bank appears here once it is verified.
Amazon Web Services (AWS) sets the exam content, timing and policy. Those details are restated from the issuer's published material and can change between versions — treat the issuer's own page as the authority for your attempt.
Case-study and scenario essay practice, lab environments and hands-on performance exams are outside written-MCQ practice and are not claimed here.
Questions
Not yet. The AWS ML Specialty question bank does not exist today, so we are not advertising practice sessions that would open onto an empty screen. The data & ai syllabus, exam pattern and eligibility are published here now, and the bank will be listed as soon as its questions pass verification.
AWS Certified Machine Learning – Specialty is examined across these areas: ML business problem framing, Data engineering and feature engineering, Model training, tuning and evaluation and Model deployment and responsible AI governance. A proctored exam of scenario-based multiple-choice items across the ML specialty blueprint, covering the full lifecycle from framing through deployment.
AWS recommends preparation through the developer and data-analytics associate or professional exams; these are recommendations rather than enforced prerequisites. Amazon Web Services (AWS) is the authority for the criteria that apply to your attempt.
Recertification follows AWS's published cycle for the credential.