CompTIA DataX

Guaranteed to Run
Price
$2,495.00
Duration
5 Days
Delivery Methods
Virtual Instructor Led Private Group
Delivery
Virtual
EST
Description
Objectives
Prerequisites
Content
Course Description

Data science is transforming industries—and CompTIA DataX proves you're ready to lead. With over 1.05 million U.S. job postings requiring data science skills and a 35% projected job growth over the next decade, the demand for skilled professionals is only accelerating.

The CompTIA DataX Certification Training course is built for experienced professionals who want to validate high-level, vendor-neutral data science skills. This course prepares you for complex real-world tasks, from optimizing machine learning models to deploying data pipelines, and aligns directly with the performance-based CompTIA DataX certification exam (DY0-001). With labs, live exercises, and hands-on projects, you'll gain the confidence to solve meaningful business problems through data.

Course Objectives

This course prepares experienced professionals seeking to validate their expertise in advanced data science. You’ll master practical skills, prepare for the CompTIA DataX certification exam, and gain confidence in deploying real-world solutions.

  • Apply mathematical and statistical techniques, including linear algebra and calculus, in business contexts
  • Navigate the data science lifecycle, from collection and transformation to communication and deployment
  • Build and refine predictive models using machine learning and deep learning techniques
  • Apply CI/CD, DevOps, and MLOps for enterprise-grade data processing workflows
  • Demonstrate your readiness for the CompTIA DataX DY0-001 certification exam
Who Should Attend?

This course is for data scientists, ML engineers, quantitative analysts, and other experienced professionals seeking to validate advanced data science skills. You should have at least five years of hands-on experience with data analysis, modeling, and deployment.

Course Prerequisites
  • 5+ years of experience in data science, computer science, or a related field
  • Strong foundational knowledge in statistics, mathematics, and machine learning.
Course Content
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: Utilizing Unsupervised Learning
Module 8: Navigating Model Selection
Module 9: Employing Machine Learning Methods
Module 10: Experimenting with Deep Learning
Module 11: Evaluating and Refining Data Models
Module 12: Communicating for Business Impact
Module 13: Deploying Data Models
Module 14: Discovering Specialized Applications
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