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  1. Programs
  3. Artificial Intel and Machine Learning

Artificial Intel and Machine Learning

Saint Cloud State University

Post-Baccalaureate CertificateAcademic

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

Apply principles of Artificial Intelligence and Machine Learning to current problems.

Credits

15 credits

Format

In-Person

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Program Pathways

Credentials this program stacks toward

No program pathways.

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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.

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Locations

Where this program is offered

  • Minnesota

    Minnesota

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Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 15-2051.00

Skills

Critical ThinkingActive ListeningComplex Problem SolvingSpeakingReading ComprehensionJudgment and Decision MakingWritingActive LearningOperation and ControlMonitoringOperations MonitoringCoordination

Knowledge

MathematicsComputers and ElectronicsEnglish LanguageEngineering and TechnologyCustomer and Personal ServiceMechanicalProduction and ProcessingDesign

Abilities

Arm-Hand SteadinessManual DexterityFinger DexterityControl PrecisionProblem SensitivityDeductive ReasoningSelective AttentionNear VisionOral ComprehensionInformation Ordering

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
  • Calculate dimensions or tolerances, using instruments, such as micrometers or vernier calipers.
  • Machine parts to specifications, using machine tools, such as lathes, milling machines, shapers, or
  • Measure, examine, or test completed units to check for defects and ensure conformance to specificati

Technology

Business intelligence and data analysis softwareData base user interface and query softwareStorage networking softwareCloud-based management softwareProcedure management softwareComputer aided design CAD softwareAnalytical or scientific softwareComputer aided manufacturing CAM softwareIndustrial control softwareEnterprise resource planning ERP software

Tools

3-axis computerized numerical control CNC machinesAdjustable wrenchesAngle platesAngled feeler gaugesAnvilsArbor pressesAviation snipsBall peen hammersBandsawsBeverly shearsBinocular light compound microscopesBoring barsBoring toolsBrake pressesBrass hammers

Work Values

SupportWorking ConditionsIndependenceAchievementRecognitionRelationships
Career Pathways

Occupations this program prepares you for

Auto-populated·from O*NET + BLS
Occupations matched to this program, with median wage, top wage, growth, and openings
SOCOccupationMethodWageGrowthOpenings
Match confidence: high15-2051.00Data Scientiststitle_inference$112,590 median$194,410 top+33.51%8,250
Match confidence: high51-4041.00Machiniststitle_inference$56,150 median$78,760 top+0.03%0
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: proficient (Level 3)(based on Post-Baccalaureate Certificate)

  • Complex, non-routine system and program malfunctions — diagnose root causes autonomously and implement durable fixes across interconnected data systems in enterprise environments.
  • End-to-end analytical solutions for strategic business problems — design and deliver, integrating data from disparate sources using advanced modeling and business intelligence platforms.
  • Machine learning and predictive models — develop, deploy, and monitor at full production scale, exercising independent judgment on algorithm selection and validation strategy.
  • Data infrastructure spanning databases, cloud services, and storage networks — architect and optimize to ensure reliability, performance, and security across the organization.
  • Ambiguous, high-stakes analytical questions — frame, investigate, and resolve by applying inductive and deductive reasoning across novel data environments.
  • Cross-functional teams and senior stakeholders — advise by translating complex quantitative findings into accessible recommendations through expert oral and written communication.
  • Procedure management and content workflow software — configure and govern to standardize data science processes and ensure consistency of analytical outputs.
  • Ethical, legal, and technical risks in data projects — evaluate with high attention to detail and integrity, applying cautious judgment before deployment decisions.
  • Custom analytical tools and automation scripts — engineer independently within development environments to accelerate team productivity on recurring research tasks.
  • Organizational data literacy gaps — assess and address by designing training materials and knowledge-sharing sessions that build analytical capability across user groups.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Completion Rate
Not reported
Placement Rate
Not reported