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  1. Programs
  2. Deep Learning in AI and Robotics

Deep Learning in AI and Robotics

University of Utah

Post-Baccalaureate CertificateAcademic

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

The Deep Learning Certificate Program will provide working knowledge of the use of state-of-the-art deep learning technology as a graduate student certificate program. Deep learning allows the identification of objects in images, translating languages and driving cars autonomously. Deep Learning is rapidly gaining application across all industries due to the availability of adequate computing power (e.g., GPUs) and large data sets to train with.

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

  • Utah

    Utah

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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 17-2199.08

Skills

Critical ThinkingMonitoringComplex Problem SolvingReading ComprehensionActive ListeningJudgment and Decision MakingSystems AnalysisWriting

Knowledge

Engineering and TechnologyDesignComputers and ElectronicsMechanicalMathematics

Abilities

Problem SensitivityOral ComprehensionWritten ComprehensionDeductive ReasoningInductive ReasoningInformation OrderingOral ExpressionWritten ExpressionFluency of IdeasOriginality

Tasks

  • Review or approve designs, calculations, or cost estimates.
  • Process or interpret signals or sensor data.
  • Debug robotics programs.

Technology

Data base user interface and query softwareContent workflow softwareComputer aided design CAD softwareIndustrial control softwareDevelopment environment software

Tools

Bar code readersDesktop computersDigital video camerasFunction generatorsLaptop computersLaser scannersMultimetersOscilloscopesProgrammable logic controllers PLCSignal conditionersSonar ringsTorque metersVision systemsWelding gun torches

Work Values

Working ConditionsIndependenceAchievementRecognitionSupportRelationships
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: medium17-2199.08Robotics Engineerstitle_inference———
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)

  • Autonomous robotic system designs — lead end-to-end, specifying architecture for computer vision, advanced sensing, and vehicle control subsystems across full project scope.
  • Complex robotic programs and motion sequences — debug and optimize autonomously, resolving non-routine faults in integrated multi-axis systems within live production or field environments.
  • End-of-arm tooling — design from first principles, selecting materials and actuation methods to meet precision, payload, and cycle-time requirements for specialized industrial applications.
  • Sensor signal processing pipelines — design and validate for real-time performance, integrating data from vision, force-torque, and proprioceptive sensors in autonomous robotic platforms.
  • Design reviews, technical calculations, and cost estimates — evaluate and approve across project deliverables, exercising independent engineering judgment to ensure compliance with safety and performance standards.
  • Technical support escalations and root-cause analyses — resolve for complex robotic system failures, producing written findings and corrective action plans distributed to cross-functional stakeholders.
  • Build, integration, and system-level acceptance testing — plan and execute for novel robotic platforms, interpreting results to authorize deployment in high-consequence environments.
  • Advanced robotics software stacks — develop and maintain using compiler tools, version control systems, and CI pipelines, ensuring code quality and traceability across release cycles.
  • Robotics system performance — monitor continuously using operations-monitoring tools and quality control analysis methods, identifying drift or degradation before system failure occurs.
  • Active learning strategies and knowledge transfer — apply independently to rapidly assimilate emerging robotics technologies, integrating new methods into existing design and development workflows.

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