CompTIA Data X

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Course Overview

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.

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 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

Course Outline

Module 1: Illustrating the Data Science Lifecycle

  • CRISP-DM and other common lifecycle frameworks
  • Folder structures, APIs, and code quality
  • Intro to R/Python syntax
  • Live Lab: Exploring the DataX Environment
  • Module Quiz

Module 2: Analyzing Business Problems

  • Identifying business needs and solutions
  • Cost-benefit analysis and model selection
  • Privacy, masking, and ethical considerations
  • Challenge Lab: Predictive Cost Modeling
  • Module Quiz

Module 3: Collecting Data

  • Structured vs unstructured data
  • Synthetic data, lineage, and ingestion
  • Pipelines, storage, and error handling
  • Live Lab: Data Ingestion Optimization
  • Module Quiz

Module 4: Cleaning and Preparing Data

  • Wrangling, transformation, and feature engineering
  • Data processing infrastructure and scaling
  • Challenge Lab: EDA for Anomaly Detection
  • Module Quiz

Module 5: Describing Data Features

  • Time series, lag, seasonality, and granularity
  • Matrix/vectorization and multivariate issues
  • Challenge Lab: Feature Interpretation
  • Module Quiz

Module 6: Exploring Data

  • EDA tasks, visualization, and statistical analysis
  • Regression tests and probability distributions
  • Module Quiz

Module 7: Utilizing Unsupervised Learning

  • Clustering, dimensionality reduction, and heuristics
  • Live Lab: Cluster Analysis for User Behavior
  • Module Quiz

Module 8: Navigating Model Selection

  • Research reviews, constraints, and mathematical and statistical techniques
  • Apply linear algebra and calculus in modeling
  • Time series forecasting and survival analysis
  • Challenge Lab: Longitudinal Prediction
  • Module Quiz

Module 9: Employing Machine Learning Methods

  • Supervised, unsupervised, and ensemble learning
  • Drift monitoring and model tuning
  • Live Labs: Logistic Regression, Decision Trees, Random Forests
  • Module Quiz

Module 10: Experimenting with Deep Learning

  • Neural networks, layers, and activation functions
  • Embeddings, OCR, and image classification
  • Challenge Lab: Deep Learning Image Processing
  • Module Quiz

Module 11: Evaluating and Refining Data Models

  • Optimization, hyperparameter tuning, and benchmarking
  • Bandits, resource allocation, and prediction accuracy
  • Live Lab: Model Optimization
  • Module Quiz

Module 12: Communicating for Business Impact

  • Storytelling, stakeholder alignment, and data compliance
  • Challenge Lab: Reporting for Decision Makers
  • Module Quiz

Module 13: Deploying Data Models

  • CI/CD, virtualization, containerization, and monitoring
  • Infrastructure-as-Code and hybrid/edge deployments
  • Live Lab: Deploy ML Pipelines in AWS
  • Module Quiz

Module 14: Discovering Specialized Applications

  • Specialized applications: NLP, computer vision, graph analytics
  • Event detection, signal processing, edge AI
  • Module Quiz

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Class Dates & Times

Class times are listed Mountain time

This is a 5-day class

Price: $2,495.00

Class dates not listed.
Please contact us for available dates and times.