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AWS · MLA-C01 Live on the App Store

MLA-C01 AWS Certified Machine Learning Engineer – Associate

Cloud Certification Practice

Updated against the official MLA-C01 exam guide

1,100+
Questions
130 min
Exam length
720
Passing score
$150
Exam cost

What is the AWS Certified Machine Learning Engineer – Associate (MLA-C01)?

The AWS Certified Machine Learning Engineer – Associate (MLA-C01) is a associate-level certification from AWS. The exam is 130 minutes long with 65 questions . The exam fee is $150 USD . StudyKits ships 1,100 questions mapped to the official exam blueprint, with detailed explanations, exam simulation, and FSRS spaced repetition — all offline.

Questions
65
Duration
130 min
Passing
720
Exam fee
$150
What you'll get

Everything you need to pass MLA-C01

Prepare confidently for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam. ML Prep provides hundreds of carefully crafted practice questions covering all four exam domains.

◆ COMPREHENSIVE COVERAGE • practice sets covering all exam domains • Data Preparation for ML (28%) • ML Model Development (26%) • Deployment and Orchestration (22%) • ML Monitoring, Maintenance & Security (24%)

◆ REALISTIC EXAM EXPERIENCE • Timed practice mode simulating the 170-minute exam • Single and multiple-choice questions in exam format • Domain-weighted question distribution matching the real exam • Exam readiness score to track your progress

◆ SMART STUDY TOOLS • Detailed explanations with AWS services and best practices • Spaced-repetition flashcards powered by FSRS algorithm • Bookmarks for quick review • Personal notes on any question • Per-domain accuracy to identify weak areas • Shuffle mode for varied practice

◆ STUDY GUIDE • Complete guide covering all exam topics • SageMaker, Bedrock, Feature Store, Model Monitor • Data pipelines, feature engineering, hyperparameter tuning • MLOps, model deployment, drift detection, security

◆ MULTILINGUAL • Available in English, Japanese, Korean, German, and Portuguese • Switch language anytime in settings

◆ PRIVACY & OFFLINE • Works completely offline — no internet required • Your progress stays on your device • No ads, no tracking

Start with free practice sets. Unlock all sets with a one-time purchase — no subscription.

Screenshots

See the app in action

Exam blueprint

MLA-C01 domains covered

Question distribution mirrors the official exam blueprint.

Domain Weight
Data Preparation for ML
28%
ML Model Development
26%
Deployment and Orchestration
22%
ML Solution Monitoring, Maintenance, and Security
24%
Why this app

Why StudyKits for MLA-C01

SageMaker depth

Built-in algorithms, hyperparameter tuning, and pipelines covered with realistic data scenarios.

Detailed explanations

Every question links the answer to the underlying service, doc, or framework — no fluff.

Realistic exam simulation

Timed sets match the real exam length, with a readiness score after each attempt.

Fully offline

All questions ship with the app. No network needed after install — study on the subway, on a flight.

Pricing

Free to start. Pro for the full bank.

One-time in-app purchase. No subscription, no auto-renewal.

Free

$0

Forever, no time limit

  • First 3 question sets
  • Detailed explanations
  • Domain-by-domain accuracy
  • No ads, no tracking

Pro

Recommended

$3.99

One-time per certification

  • Full 1,100 bank
  • Timed exam simulation
  • Spaced-repetition flashcards
  • Bookmarks + personal notes
  • Lifetime updates for MLA-C01

Pricing shown in USD. Final price reflects your local App Store currency and tax. Refunds follow the App Store / Google Play refund policy — see Terms.

FAQ

MLA-C01 questions, answered

Who is MLA-C01 for?
Engineers who build, train, and deploy ML systems on AWS — not pure researchers. Strong overlap with data engineering and MLOps work.
Do I need a maths background?
Some statistics and linear-algebra intuition helps, but the exam emphasises pipelines, deployment, and ops over derivations.
How does MLA differ from MLS-C01?
MLA-C01 (Associate) replaces MLS-C01 (Specialty). The new Associate is broader, less algorithm-heavy, and more pipelines-and-ops oriented.
How many study hours?
80–120 hours for engineers with prior ML or data work. Plan extra time for SageMaker hands-on if you have not used it.
Does the app cover Bedrock and generative AI?
Yes — Bedrock is in scope for MLA-C01 alongside SageMaker. The app covers both, with separate domain weighting.
Should I take SAA first?
Not required, but SAA-C03 builds the AWS architecture vocabulary you will reuse. If you already know AWS basics, MLA stands alone.
Related reading

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