John Wiley & Sons

CompTIA DataX Study Guide Specialization

John Wiley & Sons

CompTIA DataX Study Guide Specialization

Prepare for CompTIA DY0-001 Exam.

Master foundational data science skills, statistics, and machine learning for career growth

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Beginner level

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4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand foundational data science concepts and their real-world applications

  • Apply statistical methods to analyze and interpret datasets for informed decision-making

  • Implement data ingestion, preparation, and storage techniques for machine learning and analytics

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Taught in English
Recently updated!

April 2026

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Specialization - 3 course series

Foundations of Data Science and Statistical Methods

Foundations of Data Science and Statistical Methods

Course 1, 8 hours

What you'll learn

  • Understand the fundamental concepts, workflows, and real-world applications of data science.

  • Apply basic statistical methods to analyze and interpret datasets effectively.

  • Implement data collection, ingestion, and storage techniques for structured data management.

Skills you'll gain

Category: Applied Mathematics
Category: Data Analysis
Category: Calculus
Category: Data Management
Category: Linear Algebra
Category: Data-Driven Decision-Making
Category: Interactive Data Visualization
Category: Data Quality
Category: Data Pipelines
Category: Statistics
Category: Machine Learning
Category: Probability Distribution
Category: Data Storage
Category: Data Science
Category: Data Collection
Category: Probability & Statistics
Category: Statistical Machine Learning
Category: Exploratory Data Analysis
Category: Statistical Methods
Category: Statistical Analysis

What you'll learn

  • Prepare and transform datasets using data cleaning and preprocessing techniques

  • Build and evaluate machine learning models using appropriate metrics

  • Apply model validation methods to improve prediction reliability

Skills you'll gain

Category: Artificial Neural Networks
Category: Model Optimization
Category: MLOps (Machine Learning Operations)
Category: Model Training
Category: Data Science
Category: Data Preprocessing
Category: Unsupervised Learning
Category: Data Transformation
Category: Data Processing
Category: Data Cleansing
Category: Data Analysis
Category: Model Evaluation
Category: Predictive Modeling
Category: Machine Learning
Category: Technical Communication
Category: Applied Machine Learning
Category: Supervised Learning
Category: Model Deployment
Advanced Machine Learning, Neural Networks, and NLP

Advanced Machine Learning, Neural Networks, and NLP

Course 3, 5 hours

What you'll learn

  • Master advanced supervised machine learning techniques such as regression, decision trees, and ensemble methods.

  • Understand neural network architectures and deep learning techniques for complex problem-solving.

  • Explore NLP techniques like tokenization, sentiment analysis, and word embeddings for text data processing.

Skills you'll gain

Category: Artificial Neural Networks
Category: Data Science
Category: Machine Learning Algorithms
Category: Convolutional Neural Networks
Category: Decision Tree Learning
Category: Supervised Learning
Category: Statistical Machine Learning
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Text Mining
Category: Machine Learning Methods
Category: Model Optimization
Category: Machine Learning
Category: Deep Learning
Category: Image Analysis
Category: Data Processing
Category: Natural Language Processing
Category: Advanced Analytics
Category: Computer Vision
Category: Applied Machine Learning
Category: Logistic Regression

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Instructor

Wiley-Expert Edge Course Instructors
John Wiley & Sons
50 Courses2,343 learners

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