CompTIA DataX (DataAI) (DY0-001)

CompTIA DataX (DY0-001)

DY0-001 · ● Active · Expert · CompTIA

CompTIA's most advanced data credential, rebranded to DataAI effective January 21, 2026. Validates expert-level competency in advanced data analytics, machine learning, and specialized data science operations. Exam code and content remain unchanged; certification name and digital credentials now reflect "DataAI."

Exam facts

Field	Value
Cost	$369 USD (retail); regional pricing may vary
Duration	165 minutes
Questions	90 (mixed multiple-choice and performance-based)
Passing	720 on a scale of 100–900
Format	Multiple-choice + Performance-based questions (PBQs)
Delivery	Pearson VUE OnVUE (online proctor) or testing center
Languages	English, Japanese
Valid	3 years
Renewal	Continuing education (CE) credits or retake exam
Prerequisites	None formal; 5+ years hands-on data science or related analytics role recommended
Released	July 25, 2024
Retiring	Not scheduled (estimated 3-year lifecycle through July 2027)

Vendor source — CompTIA DataAI Certification ↗ Official exam guide — DataX Certification Guide (Online Version) ↗ Exam objectives — DY0-001 Exam Objectives ↗

About

CompTIA DataX is the vendor-neutral expert certification for senior data scientists and machine learning engineers. Launched July 25, 2024, it validates advanced competency in mathematical and statistical methods, machine learning, data operations, and specialized applications. On January 21, 2026, CompTIA rebranded the certification as "DataAI" to reflect the convergence of data science and artificial intelligence; the exam code (DY0-001), content, and rigor remain unchanged. Candidates must demonstrate 5+ years of hands-on data science experience.

Domain context — Data & Advanced Analytics

Advanced analytics, machine learning engineering, and data science operations. Spans statistical modeling, deep learning frameworks, real-time data pipelines, and specialized domain applications (healthcare, fintech, geospatial, NLP).

Topics covered

Per official CompTIA exam blueprint:

Domain 1: Mathematics & Statistics (17%)
- Data processing and cleaning
- Statistical modeling and hypothesis testing
- Linear algebra and calculus concepts
- Probability and distributions
Domain 2: Modeling, Analysis, and Outcomes (24%)
- Exploratory data analysis (EDA)
- Appropriate selection of analysis and modeling methods
- Model evaluation and justification
- Impact assessment and outcome validation
Domain 3: Machine Learning (24%)
- Supervised and unsupervised learning models
- Deep learning and neural networks
- Feature engineering and selection
- Model deployment and inference
Domain 4: Operations & Processes (22%)
- Data pipelines and workflow orchestration
- Version control and reproducibility
- Monitoring, logging, and observability
- Governance, compliance, and data ethics
Domain 5: Specialized Applications (13%)
- Natural language processing (NLP)
- Computer vision and image analysis
- Time-series forecasting
- Domain-specific applications (healthcare, finance, IoT)

Source: Official DY0-001 Exam Objectives ↗

Common skills at Data & Advanced Analytics · Expert

Shared competencies for the Data & Advanced Analytics domain at Expert level.

Advanced statistical modeling and hypothesis testing design
Deep learning architecture design and optimization
End-to-end machine learning pipeline engineering
Production data infrastructure and MLOps
Real-time data processing and streaming systems
Advanced feature engineering and selection methodologies

Recommended courses at Data & Advanced Analytics · Expert

Provider	Title	Cost	URL
CompTIA (Official)	CertMaster Perform for DataX DY0-001	$299–$399	↗
CompTIA Training	CertMaster Labs for DataX DY0-001	Included with Perform	↗
Udemy	Ultimate CompTIA DataX (DY0-001) Practice Exams (2025)	$12–$80	↗
Udemy	CompTIA DataX (DY0-001) Certification Prep	$12–$80	↗
CBT Nuggets	CompTIA DataAI (DY0-001) Training	$399–$599/year	↗
Pluralsight	CompTIA DataX Certification Path	$299–$399/year	Available via Pluralsight subscription
LinkedIn Learning	Machine Learning Foundations + Data Science Specialization	$32.99/month	↗

Practice exams

Provider	Title	Cost	URL
Sybex (Official study companion)	CompTIA DataX Study Guide — 2 Practice Exams	Included ($50–$65 book)	↗
CompTIA CertMaster Perform	Official practice exams and PBQs	$299–$399	↗
Udemy	Ultimate CompTIA DataX (DY0-001) Practice Exams	$12–$80	↗
Whizlabs	CompTIA DataX Practice Tests	$49–$99	Available via Whizlabs platform

Books

Title	Author	Publisher	Year	ISBN	URL
CompTIA DataX Study Guide: Exam DY0-001	Fred Nwanganga	Sybex (Wiley)	2024	978-1394238989	↗

Note: The Nwanganga Sybex Study Guide (published August 2024) is the current standard reference for DY0-001 and includes two full practice exams and interactive online tools.

Typical job titles at Data & Advanced Analytics · Expert

Senior Data Scientist · Machine Learning Engineer · AI Engineer · ML Platform Engineer · Data Science Lead · Principal Data Scientist

(Job titles drawn from job-board postings listing DY0-001 or equivalent expertise as required/preferred.)

Salary

Region	Range	Source
USD	$175,000–$240,000 (senior engineer base); $320,000–$550,000+ (FAANG/top-tier total comp)	Glassdoor ↗ · Coursera Salary Guide ↗ · Signify Technology Benchmarks ↗
ZAR	R822,000–R1,100,000	Glassdoor ZA ↗ · PayScale ZA ↗
GBP	£70,000–£95,000 (senior); £100,000–£130,000+ (principal/leadership)	IT Jobs Watch ↗ · Robert Half UK ↗ · Glassdoor UK ↗

Salary note: DY0-001 targets experts with 5+ years experience, commanding premium salaries. USD figures reflect 2025–2026 market data; specialization in GenAI/LLM fine-tuning commands 40–60% premiums over baseline.

Skills validated

Concrete technologies and methodologies tested by DY0-001.

Python, R, SQL, and Scala for data science workflows
Jupyter Notebooks and RMarkdown for reproducible research
Scikit-learn, TensorFlow, PyTorch, and XGBoost
Pandas, NumPy, and other numerical computing libraries
Statistical hypothesis testing and experimental design
Supervised learning: regression, classification, ensemble methods
Unsupervised learning: clustering, dimensionality reduction
Deep learning: CNNs, RNNs, transformers, attention mechanisms
Time-series analysis and ARIMA/Prophet forecasting
Natural language processing: tokenization, embeddings, transformers
Data pipeline orchestration: Airflow, Kubernetes, Spark
Model evaluation: cross-validation, hyperparameter tuning, fairness/bias auditing
Production ML: containerization (Docker), model serving, monitoring
Data governance: compliance, lineage, documentation, ethics

Related certifications

Prerequisite for: None; CompTIA has not announced higher-tier certifications beyond DataX/DataAI
Complements: AWS Certified Machine Learning Engineer Associate ↗ (cloud-specific ML focus)
Complements: Google Cloud Professional Machine Learning Engineer ↗ (GCP-specific)
Complements: Microsoft Certified: Azure Data Scientist Associate ↗ (Azure/Fabric data science)
Vendor overview: CompTIA Vendor Overview ↗

Sources

Last verified: 2026-05-01 Parent ecosystem: Data Science & Machine Learning Parent domain: Data & Advanced Analytics Vendor overview: CompTIA Vendor Overview