CompTIA DataAI: The Reimagined DataX Certification for the Advanced Data and AI Workforce.

CompTIA DataAI (formerly DataX) is the premier certification for highly experienced professionals seeking to validate competency in the rapidly evolving field of data science. DataAI equips you with the skills to precisely and confidently demonstrate expertise in handling complex data sets, implementing data-driven solutions, and driving business growth through insightful data interpretation.

Explore the top Data and AI certifications for 2026. Be the professional businesses are searching for—get certified today!

Overview

CompTIA DataAI is an expert-level certification designed for experienced data professionals ready to work at the intersection of data science, AI, and enterprise operations.

The certification targets senior data analysts, data scientists, data engineers, and IT professionals who are already working with analytics, cloud platforms, and AI-enabled tools—and who want to move into more advanced, AI-infused roles.

Aligned with CompTIA’s Xpert Series, DataAI reflects how advanced data roles have evolved. Statistical rigor, machine learning, MLOps, and business outcomes are no longer separate concerns. The certification confirms that a professional can move beyond analysis into building trustworthy, scalable AI systems that deliver measurable results.

Skills Covered

CompTIA DataAI ensures learners have skills around:

  • Mathematics and Statistics: Apply mathematical and statistical methods appropriately and understand the importance of data processing and cleaning, statistical modelling, linear algebra, and calculus concepts.
  • Modeling, Analysis and Outcomes: Utilize appropriate analysis and modeling methods and make justified model recommendations.
    Machine Learning: Apply machine learning models and understand deep learning concepts.
  • Operations and Processes: Understand and implement data science operations and processes.
  • Specialized Applications of Data Science: Demonstrate understanding of industry trends and specialized data science in various fields.

Prerequisites

Having a minimum of five years of hands-on experience as a data scientist or the equivalent knowledge is strongly recommended.

Target Audience

This course is designed for data science professionals who are seeking to validate and expand their skillsets. Primary job roles:

  • Data Scientists
  • Quantitative Analyst
  • Machine Learning Engineer/Specialist
  • Predictive Analyst
  • Artificial Intelligence (AI) Engineer

Course Curriculum

Course Outline

  • Module 1: Illustrating the Data Science Lifecycle
  • Module 2: Analyzing Business Problems
  • Module 3: Collecting Data
  • Module 4: Cleaning and Preparing Data
  • Module 5: Describing Data Features
  • Module 6: Exploring Data
  • Module 7: Navigating the Model Selection Process
  • Module 8: Employing Machine Learning Methods
  • Module 9: Experimenting with Deep Learning
  • Module10: Evaluating and Refining Data Models
  • Module 11: Communicating for Business Impact
  • Module 12: Deploying Data Models
  • Module 13: Discovering Specialized Data Science Applications

Dates & Locations

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June 22, 2026 - June 26, 2026

Location: Kuala Lumpur
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RM 2381
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June 22, 2026 - June 26, 2026

Location: Kuala Lumpur
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September 7, 2026 - September 11, 2026

Location: Kuala Lumpur
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RM 2381
RM 4500

September 7, 2026 - September 11, 2026

Location: Kuala Lumpur
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RM 2381
RM 4500

December 14, 2026 - December 18, 2026

Location: Kuala Lumpur
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Exam:
RM 2381
RM 4500

December 14, 2026 - December 18, 2026

Location: Kuala Lumpur
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Exam:
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Exam & Certification

CompTIA DataAI (DY0-001)

The CompTIA DataAI exam was developed to meet an industry need ––bridge gaps in training and knowledge for data science professionals. The exam objectives include real-world scenarios where learners apply their knowledge, ensuring they are prepared for various challenges they may face in their careers as data scientists.

Based on extensive input from experienced data scientists, DataAI validates successful candidates can properly utilize and analyze vast amounts of data, extract meaning and generate actionable insights. Successful DataAI candidates gain the skills and knowledge required to:

  • Understand and implement data science operations and processes.
  • Apply mathematical and statistical methods appropriately and understand the importance of data processing and cleaning, statistical
    modeling, linear algebra and calculus concepts.
  • Apply machine learning models and understand deep learning concepts.
  • Utilize appropriate analysis and modeling methods and make justified model recommendations.
  • Demonstrate understanding of industry trends and specialized data science applications.

Training & Certification Guide

  • Launch date: July 2024
  • Number of questions: Maximum of 90 questions per exam
  • Type of questions: Multiple choice
  • Length of test: 165 minutes
  • Passing score: Pass/Fail Only (No scaled score)
  • Retirement: usually three years after launch (estimated 2027)

  • Mathematics and Statistics: 17%
  • Modeling, Analysis, and Outcomes: 24%
  • Machine Learning: 24%
  • Operations and Processes: 22%
  • Specialized Applications of Data Science: 13%

Total: 100%

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Data and AI: How AI is Used in Data Analytics

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As such, we’re thrilled to announce the launch of our Microsoft AI Mastery Program in 2024, made possible through our partnership with Microsoft, a renowned leader in AI technology. This program is tailored for individuals and tech professionals pass

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Frequently Asked Questions

The rebrand from DataX to DataAI reflects how fundamentally the data profession has changed. Advanced analytics, machine learning, automation, and cloud-native platforms are now standard components of enterprise data environments. Data science and AI are inseparable in practice, and the skills required go far beyond traditional analytics or reporting.

Renaming the certification to DataAI makes that shift explicit, signaling this as an AI-centric, expert-level credential designed for professionals who are building, deploying, and optimizing AI-driven data solutions.

CompTIA DataAI builds directly on the foundation established by DataX while updating emphasis to reflect AI-driven, production-ready data work. The core structure remains intact, organized across five domains: mathematics and statistics; modeling, analysis, and outcomes; machine learning; operations and processes; and specialized applications of data science.

What has changed is focus and weighting. DataAI places greater emphasis on AI, machine learning, and operational execution. Objectives align more closely with real-world tasks such as selecting and evaluating models, deploying systems through MLOps, and translating analytical results into measurable business value. The updated exam reflects modern AI workflows, governed data pipelines, cloud platforms, and the realities of running models reliably at scale.

The rigor remains expert-level, but the content is more explicitly AI-focused. DataAI is built around advanced roles, including data scientist, senior data analyst, machine learning engineer (data-focused), AI data specialist, and advanced analytics lead.

CompTIA DataAI is designed to help experienced professionals move into higher-impact roles as organizations deepen their use of AI and advanced analytics. For individuals, the certification supports career progression by validating readiness for promotions, lateral moves into data science leadership, and participation in strategic, business-critical initiatives.

For employers, DataAI provides assurance that teams possess the expertise to design, implement, and operate AI-driven data solutions responsibly and at scale. It strengthens workforce readiness as data, AI, and security converge across enterprise and government environments.

Professionals in the data field looking to upskill and close existing knowledge gaps will benefit from CompTIA DataX. This new certification falls under CompTIA Xpert — a new series of certifications and trainings offered through CompTIA that are geared towards professionals who are looking to gain expert knowledge in business-critical technologies.

DataX equips highly experienced professionals with essential skills that meet the demands of the rapidly evolving field of data science. Learners will have access to a comprehensive curriculum that covers concepts ranging from the foundations of machine learning to more specialized data science applications.

While covering these emerging concepts, learners won’t spend time revisiting familiar concepts that they’ve already encountered in their careers. Instead, DataX helps learners focus their efforts on filling existing knowledge gaps due to a lack of available training.

CompTIA DataAI is important because it validates expert-level data science skills regardless of vendor tools. It equips professionals to interpret and visualize data effectively, meeting the growing demand for data-driven decision-making across industries with globally recognized credibility.

No. The name change does not affect the certification status of DataX holders. Active CompTIA DataX certification holders continue to be recognized under the new CompTIA DataAI name, with no additional action or testing required.

CompTIA DataAI is ISO/ANSI National Accreditation Board (ANAB) accredited, which ensures it meets global certification standards. This accreditation makes it a trusted credential for data professionals worldwide, demonstrating validated skills and knowledge in data analysis across various industries and regions.

CompTIA DataAI certification is good for three years from the date of your certification exam. The CE program allows you to extend your certification in three-year intervals through activities and training that relate to the content of your professional certification.

With CompTIA DataAI certification, you can pursue roles like data analyst, business intelligence analyst, market research analyst, operations analyst, or financial analyst. It validates data analysis skills, opening opportunities across industries like technology, finance, healthcare, and more.

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