• Exam Breakdown
  • Domain Breakdown
  • Access Breakdown

Exam Format

  • Exam Code: DY0-001 DataAI
  • Level: Advanced / Data Science Professional
  • Duration: 165 minutes
  • Passing Score: Pass/Fail only — no scaled score
  • Unscored Content: Includes trial questions that are mixed in and not identified during testing

Exam Policies

  •  Offline Proctoring: Must be rescheduled or canceled at least 24 hours before the scheduled exam time.
  •  Online Proctoring: Available via Pearson VUE remote proctoring platform.
  •  Waiting Period: No waiting period for the first retake; subsequent attempts follow CompTIA retake policy guidelines.
  •  Retake Fee: Full exam fee must be paid for each retake.

Exam Details

  • Question Types: Multiple-choice and performance-based questions 
  • Number of Questions: Maximum of 90 questions 
  • Hands-On Questions: Yes—performance-based simulations are included 

Validity

  • Certification Validity: Typically valid for 3 years before retirement or update 
  • Renewal Options: Currently not outlined—likely requires retake or replacement exam once updated

Exam Fee

  •  Base Fee: $503 USD (excluding taxes)
  •  Taxes: Country-specific VAT may apply
  •  Example: In India, 18% tax applies, making the total $593.54 USD ($503 + $90.54 tax)

Prerequisites

There are no formal prerequisites for taking the CompTIA DataAI (DY0-001) exam. However, it is strongly recommended to have:
  • Several years of experience working with data or analytics
  • Working knowledge of statistics and data analysis concepts
  • Experience with programming or scripting for data analysis
  • Familiarity with data visualization and communicating insights

Exam Topics

Exam Topics

  •  Data Engineering and Infrastructure: Data pipelines, data architecture, ETL processes
  •  Data Analysis and Modeling: Statistical analysis, predictive modeling, machine learning concepts
  •  Machine Learning Operations (MLOps): Model deployment, monitoring, and lifecycle management
  •  Data Governance and Security: Data quality, compliance, privacy, and access control
  •  Visualization and Communication: Data presentation and business insights delivery

Intended Audience

The CompTIA DataAI certification is ideal for advanced data professionals, including:
  •  Data Scientist
  •  Data Engineer
  •  Machine Learning Engineer
  •  Data Architect
  •  Senior Data Analyst

CAREER IMPACT

Jobs You Can Get:
  • Senior Data Scientist, Data Science Engineer, Machine Learning Engineer, Analytics Lead

Average Salary: Varies by country —

  • U.S.: $120,000–$180,000 USD
  • India: ₹12,00,000–₹35,00,000 INR
  • United Kingdom: £70,000–£120,000 GBP
  • UAE: 250,000–450,000 AED per year

Why It’s Valuable:

  • Advanced vendor-neutral certification validating enterprise data engineering and machine learning expertise.
 

Exam Mode

  • Available via Pearson VUE testing centers and secure online proctoring through CompTIA’s testing options. ([turn0search1])
 

Exam Booking Link

  • Register through CompTIA’s Candidate Portal under “DataAI (DY0-001)”

Once you pass the exam

  •  Access your certification through your CompTIA certification account
  •  Processing Time: Digital certificate typically available within a few days after passing
  •  Log in to your CompTIA account
  •  Navigate to the Certifications section
  •  Download your certificate and digital badge

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    Top Reasons to Choose
    CompTIA DataAI Certification Exam

    Advanced Data Engineering and AI Skills Validation

    The CompTIA DataAI certification validates advanced expertise in data engineering, machine learning, and analytics, enabling professionals to design scalable data solutions and support enterprise artificial intelligence initiatives effectively.

     
    Vendor-Neutral Expert-Level Data Certification

    This certification provides platform-independent validation of data science and engineering skills applicable across diverse technologies, increasing professional credibility and career opportunities in modern data-driven organizations.

     
    Growing Demand for Data and AI Professionals

    Organizations increasingly rely on artificial intelligence and data analytics for strategic decisions, creating strong demand for professionals with advanced data engineering and machine learning expertise across industries worldwide.

     

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    FAQ

    • Who should take the CompTIA DataAI exam?

      The CompTIA DataAI exam is designed for experienced data professionals responsible for designing and managing data solutions. It is ideal for data engineers, data scientists, and machine learning specialists who want to validate advanced skills in data modeling, analytics, and enterprise data infrastructure management.

    • How difficult is the CompTIA DataAI exam?

      The CompTIA DataAI exam is considered highly challenging because it tests advanced data engineering, machine learning, and analytics concepts. Candidates must understand data pipelines, modeling techniques, and enterprise data architecture. Significant hands-on experience and structured preparation are recommended for successful certification outcomes.

    • Why does CompTIA offer the DataAI certification?

      CompTIA offers the DataAI certification to validate advanced data science and engineering expertise required in modern enterprises. The credential helps organizations identify professionals capable of building data-driven solutions, managing large-scale data environments, and implementing machine learning technologies effectively.

    • What tools and resources can be used to prepare for the CompTIA DataAI exam?

      Candidates can prepare using CompTIA official study materials, practice exams, online training, and hands-on experience with data engineering tools, machine learning frameworks, and analytics platforms. Reviewing data architecture, modeling techniques, and MLOps practices significantly improves exam readiness and technical proficiency.

    • Is the CompTIA DataAI certification still valuable in 2026?

      Yes, the CompTIA DataAI certification remains valuable in 2026 as organizations increasingly adopt artificial intelligence and data-driven strategies. The credential validates advanced data expertise, enhances professional credibility, supports high-level data careers, and provides strong recognition in enterprise data and analytics roles worldwide.