CompTIA DataX (Preparation for Exam DY0-001)

During this course, students will learn:

• 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 applications.
 

• Data Scientist
• Quantitative Analyst
• Machine Learning Engineer/ Specialist
• Computer & Information Research Scientist

5+ years of experience in data science or a similar role is recommended.
 

Mathematics and Statistics 17%

• Given a scenario, apply the appropriate statistical method or concept.
• Explain probability and synthetic modeling concepts and their uses.
• Explain the importance of linear algebra and basic calculus concepts.
• Compare and contrast various types of temporal models.

Modeling, Analysis and Outcomes 24%

• Given a scenario, use the appropriate exploratory data analysis (EDA) method or process.
• Given a scenario, analyze common issues with data.
• Given a scenario, apply data enrichment and augmentation techniques.
• Given a scenario, conduct a model design iteration process.
• Given a scenario, analyze results of experiments and testing to justify final model recommendations and selection.
• Given a scenario, translate results and communicate via appropriate methods and mediums.

Machine Learning 24%

• Given a scenario, apply foundational machine-learning concepts.
• Given a scenario, apply appropriate statistical supervised machine-learning concepts.
• Given a