Data Science for Beginners | SUNY College of Technology at Canton

Skills & Competencies

Skills developed through this program

Auto-populatedfrom O*NET via SOC 15-2051.00

Skills

Critical ThinkingReading ComprehensionActive ListeningComplex Problem SolvingSpeakingJudgment and Decision MakingWritingActive Learning

Knowledge

Computers and ElectronicsEnglish LanguageMathematicsEngineering and TechnologyCustomer and Personal Service

Tasks

Troubleshoot program and system malfunctions to restore normal functioning.
Provide staff and users with assistance solving computer-related problems, such as malfunctions and
Test, maintain, and monitor computer programs and systems, including coordinating the installation o

Technology

Business intelligence and data analysis softwareData base user interface and query softwareStorage networking softwareCloud-based management softwareProcedure management software

Career Pathways

Occupations this program prepares you for

Auto-populatedfrom O*NET + BLS

Occupations matched to this program, with median wage, top wage, growth, and openings
SOC	Occupation	Method	Wage	Growth	Openings
Match confidence: high15-2051.00	Data Scientists	title_inference	$112,590 median$194,410 top	+33.51%	8,250

Program Pathways

Credentials this program stacks toward

No program pathways.

What You'll Learn

Key competencies developed through this program

Auto-populatedfrom NSX Competency Framework

Mastery: emerging (Level 1)(based on Micro-Credential)

Structured datasets and query tools — retrieve and inspect using standard SQL commands under direct supervisor guidance in a business analytics environment.
Program malfunctions and error logs — identify and document following established troubleshooting checklists on assigned data pipelines.
Business intelligence dashboards — interpret pre-built visualizations and summarize findings in written reports for team review.
Statistical software and development environments — execute provided scripts and record outputs under close mentorship during onboarding projects.
Data quality issues and anomalies — recognize and escalate using defined protocols within a structured data governance workflow.
Database management systems — navigate and perform basic queries following documented procedures on production or staging environments.
Computer program installation and configuration — assist senior staff in coordinating and testing setup steps according to written runbooks.
Technical findings and data summaries — communicate clearly in team meetings using active listening and structured speaking techniques.
Mathematical and statistical concepts — apply foundational methods such as descriptive statistics to support routine analytical tasks assigned by senior data scientists.
Cloud-based management tools — operate under direction to monitor resource usage and flag irregularities for supervisor review.

Program Details

Detailed information about this program

No detailed information available.

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

No scholarships listed.