Data Scientist

Competency-based

ONET: 15-2051.00

2

Years

16

Skills

65h

Related instructions

Curriculum

Introduction to Geographic Information Systems (GIS)
Programming Fundamentals I
Cartography and Geography in Geographical Information Systems (GIS) and Global Positioning Systems
Learning Framework
Programming Fundamentals II
Introduction to Machine Learning
** College Algebra (May waive out or may have to take Developmental Algebra)
Computer Vision for Artificial Intelligence (A.I.)
Introduction to Raster-Based Geographic Information Systems (GIS)
Web-Served Geographic Information Systems (GIS)
Artificial Intelligence (A.I.) in Cybersecurity
Federal Government
Artificial Intelligence (A.I.) in Applications & Case Histories
Natural Language Processing NLP
Database Design and Theory
Robotic Operating Systems and Platforms in Artificial Intelligence (A.I.)
Deep Learning in Artificial Intelligence
Data Science in Artificial Intelligence
Introduction to Philosophy
Humanities / Fine Arts Elective (Student will select)

On-the-job training

Advise others on analytical techniques
- Recommend data-driven solutions to key stakeholders.
Analyze business or financial data
- Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
Analyze data to identify or resolve operational problems
- Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
Analyze data to identify trends or relationships among variables
- Identify relationships and trends or any factors that could affect the results of research.
Analyze data to inform operational decisions or activities
- Analyze, manipulate, or process large sets of data using statistical software.
Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields
- Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
Determine appropriate methods for data analysis
- Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
Develop procedures to evaluate organizational activities
- Design surveys, opinion polls, or other instruments to collect data
Develop scientific or mathematical models
- Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
Prepare analytical reports
- Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software
Prepare data for analysis
- Clean and manipulate raw data using statistical software.
Prepare graphics or other visual representations of information
- Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software
Present research results to others
- Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users
Select resources needed to accomplish tasks
- Identify business problems or management objectives that can be addressed through data analysis
Update technical knowledge
- Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
Write computer programming code
- Write new functions or applications in programming languages to conduct analyses