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CompTIA · AI & Machine Learning · Expert

CompTIA DataAI exam guide

Exam DY0-001

CompTIA DataAI (DY0-001), formerly DataX, is an expert-level Xpert series certification for experienced data scientists. It validates mathematics and statistics, modeling, machine learning, operations and specialized applications such as NLP and computer vision. It is vendor-neutral and pass/fail.

QuestionsUp to 90
Time limit165 minutes
Passing scorePass/fail only (no scaled score)
Exam fee$544 USD
Valid for3 years
DeliveryPearson VUE test center or online proctored (OnVUE)

Format: Multiple choice and performance-based. Fee note: 2026 US retail price; about $709 with retake.

Who it's for

Data scientists and ML practitioners with 5+ years of experience who want a vendor-neutral expert credential.

What the exam covers

Mathematics and Statistics17%
Modeling, Analysis, and Outcomes24%
Machine Learning24%
Operations and Processes22%
Specialized Applications of Data Science13%

Eligibility & prerequisites

Required: None

Recommended: 5+ years in data science or a similar role.

Keeping it active

Valid 3 years. Renew through CompTIA Continuing Education: earn 75 CEUs in the 3-year cycle and pay the $150 CE fee, or pass a newer version or a higher-level CompTIA exam that renews it automatically, or complete the matching CertMaster CE course.

Skills & careers

Skills it validates

  • Applied statistics, linear algebra and calculus for ML
  • Feature engineering and model selection
  • Supervised, unsupervised and deep learning
  • Model evaluation and communicating outcomes
  • MLOps, deployment and data pipelines
  • NLP, computer vision and other specialized techniques

Job roles

Data ScientistMachine Learning EngineerAI EngineerQuantitative AnalystSenior Data Analyst

Where it fits in your path

Planning a degree too? See how this cert earns college credit in the College Credit Navigator.

Build my study plan

  1. Week 1-2: Mathematics and statistics: distributions, hypothesis testing, linear algebra, optimization.
  2. Week 3-4: Modeling and machine learning (48% combined): regression, classification, clustering, tree ensembles, neural networks, evaluation metrics.
  3. Week 5: Operations and processes: data pipelines, deployment, monitoring, drift, governance.
  4. Week 6: Specialized applications: NLP, computer vision, time series, graph analysis.
  5. Week 7: Timed practice exams and review of metrics and model-selection scenarios.

Make it yours: pick your exam date and weekly hours. We'll split your time by domain weight and give you a printable plan.

Exam-day tips

  • Know which evaluation metric fits each problem (precision vs recall, RMSE vs MAE, AUC).
  • Expect to interpret model output, confusion matrices and residual plots.
  • Modeling and machine learning together are 48% of the exam.
  • There is no scaled score; it is pass/fail, so avoid neglecting the smaller domains.
  • Know common causes and fixes for overfitting, class imbalance and data leakage.

Key terms for this exam

All 47 terms Study with thinQcards™

Commonly confused on this exam

Frequently asked questions

Is DataAI the same as DataX?

Yes. CompTIA renamed DataX to DataAI; the exam code remains DY0-001.

How much does DataAI cost?

$544 USD at CompTIA's 2026 US retail price.

How do I renew DataAI?

Earn 75 CEUs over 3 years and pay the $150 CE fee.

DataAI vs cloud ML certs?

DataAI is vendor-neutral data science theory and practice; AWS, Google and Microsoft ML certs test their own platforms.

What is the passing score?

There is none published; results are pass/fail only.

Official page: www.comptia.org. Reviewed November 2026. Vendors change fees and objectives, so confirm with the vendor before you book. Spot something out of date? Tell us.