Artificial Intelligence Engineering (Mechanical Engineering) | Arizona State University Campus Immersion

Skills & Competencies

Skills developed through this program

Auto-populatedfrom O*NET via SOC 15-2051.00

Skills

Critical ThinkingActive ListeningJudgment and Decision MakingReading ComprehensionComplex Problem SolvingActive LearningSpeakingWritingRepairingTroubleshootingOperations MonitoringEquipment MaintenanceOperation and ControlScienceMathematics

Knowledge

Engineering and TechnologyComputers and ElectronicsEnglish LanguageCustomer and Personal ServiceMechanicalMathematicsDesignProduction and Processing

Abilities

Deductive ReasoningProblem SensitivityInductive ReasoningNear VisionOral ComprehensionInformation OrderingManual DexterityFinger DexterityArm-Hand SteadinessControl PrecisionWritten ComprehensionOral ExpressionMathematical ReasoningWritten Expression

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
Inspect vehicles for damage and record findings so that necessary repairs can be made.
Test drive vehicles and test components and systems, using equipment such as infrared engine analyze
Test and adjust repaired systems to meet manufacturers' performance specifications.
Read and interpret blueprints, technical drawings, schematics, or computer-generated reports.
Research, design, evaluate, install, operate, or maintain mechanical products, equipment, systems or
Specify system components or direct modification of products to ensure conformance with engineering
Investigate equipment failures or diagnose faulty operations and recommend or perform remedial actions.

Technology

Data base user interface and query softwareAnalytical or scientific softwareComputer aided manufacturing CAM softwareBusiness intelligence and data analysis softwareStorage networking softwareCloud-based management softwareProcedure management softwareFacilities management softwareInternet browser softwareDevelopment environment softwareGraphics or photo imaging softwareComputer aided design CAD software

Tools

2-channel lab scopes3 pound sledge hammers5 pound sledge hammers5-gas emissions analyzersAdjustable wrenchesAir chiselsAir compressorsAir conditioner chargersAir drillsAir hammersAir sandersAir wrenchesAlignment wrenchesAllen wrenchesAlternating current/direct current AC/DC inductive current clampsAccelerometersAcoustic emission AE sensorsAlignersAnalog to digital convertersAnodic wafer bonding systemsChemical-mechanical polishing equipmentComputed tomography CT systemsContact lithography equipmentContact testersCoordinate measuring machines CMMCryogenic apparatusDeep reactive ion etchers DRIEDigital particle image velocimetersDigital to analog converters

Work Values

SupportIndependenceRelationshipsAchievementWorking ConditionsRecognition

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
Match confidence: high49-3023.00	Automotive Service Technicians and Mechanics	title_inference	$49,670 median$80,850 top	+4.17%	3,360
Match confidence: high17-2141.00	Mechanical Engineers	title_inference	—	—	—

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: advanced (Level 4)(based on Master's Degree)

Enterprise-wide data science strategy and capability roadmap — define and champion, aligning analytical investments with long-term organizational objectives across all business units.
Organizational standards for model development, validation, and governance — establish and enforce, setting the technical direction that all data science practitioners follow.
Senior data scientists and cross-disciplinary teams — mentor and develop through structured coaching, performance feedback, and deliberate career growth planning.
Novel methodological approaches and innovative tool adoption — lead evaluation and institutionalization of, driving competitive differentiation through intellectual curiosity and calculated risk-taking.
Executive leadership and board-level stakeholders — advise by synthesizing complex analytical insights into strategic narratives that directly inform high-impact business decisions.
Partnerships with engineering, product, and domain leadership — orchestrate to embed data science solutions into core operational and product development workflows at scale.
Organizational risk posture for data, privacy, and algorithmic accountability — shape by developing policies and oversight mechanisms grounded in integrity and regulatory compliance.
Large-scale system overhauls and data platform modernizations — sponsor and govern, ensuring technical excellence and business continuity throughout multi-year transformation programs.
Talent acquisition pipelines and workforce development programs for data science — design and lead, ensuring the organization attracts and retains top-tier analytical professionals.
Firm-wide culture of evidence-based decision-making — cultivate by modeling rigorous critical thinking and championing data-driven practices at every level of the organization.

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.