Overview
Skills Covered
CompTIA DataX ensures learners have skills around:
- 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.
Who Should Attend
This course is designed for data science professionals who are seeking to validate and expand their skillsets. Primary job roles:
- Data Scientist
- Quantitative Analyst
- Machine Learning Engineer/Specialist
- Predictive Analyst
- Artificial Intelligence (AI) Engineer
Course Curriculum
Course Modules
Exam & Certification
CompTIA DataX (DY0-001)
The CompTIA DataX exam was developed to meet an industry need ––bridge gaps in training and knowledge for data science professionals. The exam objectives include real-world scenarios where learners apply their knowledge, ensuring they are prepared for various challenges they may face in their careers as data scientists.
Based on extensive input from experienced data scientists, DataX validates successful candidates can properly utilize and analyze vast amounts of data, extract meaning and generate actionable insights. Successful DataX candidates gain the skills and knowledge required to:
- Understand and implement data science operations and processes.
- Apply mathematical and statistical methods appropriately and understand the importance of data processing and cleaning, statistical
modeling, linear algebra and calculus concepts. - Apply machine learning models and understand deep learning concepts.
- Utilize appropriate analysis and modeling methods and make justified model recommendations.
- Demonstrate understanding of industry trends and specialized data science applications.
