CBTNuggets – CompTIA DataX (DY0-001) Online Training 2025-7

CompTIA DataX (DY0-001) Online Training. This course provides data professionals with practical skills in AI, Machine Learning, and MLOps to prepare them for the CompTIA DataX certification exam. This course is suitable for data scientists, applied statisticians, and AI engineers who have previous experience in data modeling, machine learning, and statistical programming and want to demonstrate their ability to apply data science methods in real-world environments. Participants in this course will be introduced to core concepts such as statistics, data modeling, and machine learning, and will learn how to implement Deep Learning models, build pipelines, and use Computer Vision in real-world scenarios. The DataX exam is challenging and assesses not only theoretical knowledge but also the ability to implement advanced data science concepts. Success on this exam requires proficiency in tools such as TensorFlow or PyTorch and a deep understanding of modeling and machine learning. Earning a DataX certification can increase your chances of landing lucrative jobs in AI and data analytics, as it demonstrates your ability to apply key techniques under pressure and enhances your professional credibility. This course is a great option for those looking to advance in data-related roles.

What you will learn

• Design and manage data science pipelines for machine learning.
• Applying linear algebra and calculus to Deep Learning models.
• Extraction, preparation, and transformation of data for artificial intelligence applications.
• Deploying Computer Vision and Deep Learning models in operational environments.
• Apply MLOps best practices to automate the model lifecycle.
• Convey complex AI insights to technical and non-technical teams.

This course is suitable for people who:

• IT professionals, data analysts, and developers preparing for CompTIA DataX certification and related roles in data science, machine learning, and MLOps.
• Professionals currently working in data-related roles and looking to enhance their skills.
• Data scientists, applied statisticians, or AI engineers who want to prove their skills in real-world environments.

Course details

• Publisher: CBTNuggets
• Instructor: Jonathan Barrios
• Education level: Intermediate
• Training duration: 30 hours and 7 minutes
• Number of lessons: 318

Course topics

• Explore Data Science and Resources for DataX
• Assess your Data Science Knowledge Gaps for DataX
• Explore Data Science Tools and Lifecycles
• Examine Data Science Code Syntax and Workflows
• Review Best Practices, Composition, & Requirements
• Explore Change Using Calculus for Data Science
• Apply Probability & Statistics for Data Science
• Perform Statistical Testing for Data Science
• Apply Linear Algebra to Data Science Problems
• Examine Key Data Sources for Data Science
• Explore Data Ingestion & Storage for Data Science
• Explore Data Analysis & Variables for Data Science
• Explore Multivariate Analysis and Quality in DS
• Explore Data Transformation for Data Science
• Augment and Feature Engineer Data for Data Science
• Explore Statistical and Machine Learning Models
• Validate Models and Communicate Data Effectively
• Analyze Model Deployment and MLOps
• Build a Supervised Learning Regression Model
• Build a Supervised Learning Classification Model
• Explore Quadratic and Linear Discriminant Analysis
• Classify Data with the Naive Bayes Algorithm
• Explore Decision Trees and Ensemble Methods
• Analyze Core Artificial Neural Network Concepts
• Explore ANN Training Techniques & Gradient Descent
• Apply Neural Network Concepts to Deep Learning
• Compare PyTorch and TensorFlow for Deep Learning
• Explore Natural Language Processing (NLP) Concepts
• Explore Tokenization, Gen AI, and LLMs in NLP
• Prepare Text for Natural Language Processing
• Use Advanced Text Preparation for Machine Learning
• Apply NLP One-Hot, BoW, TF-IDF, Word2Vec & GloVe
• Explore Foundations of Optimization
• Compare Linear and Nonlinear Programming Methods
• Explore Specialized Machine Learning Optimization
• Apply Computer Vision for Image Understanding
• Apply Feature Extraction for Image Perception
• Identify Knowledge Gaps with the DataX SkillScan
• Use Models to Understand IP Networking

CompTIA DataX (DY0-001) Online Training Course Images

Sample course video

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Download Part 6 – 802 MB

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File size

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