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My LER
  1. Programs
  3. AI in Biomedical Research

AI in Biomedical Research

National Institutes of Health (NIH)

Micro-CredentialCIP: 15.2041

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

A course on applying artificial intelligence and machine learning techniques to biomedical research| including data analysis and predictive modeling.

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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

No locations specified.

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Related Programs

Programs related to this one

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Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 19-4061.00

Skills

Reading ComprehensionCritical ThinkingActive ListeningWritingSpeakingComplex Problem SolvingScienceJudgment and Decision Making

Knowledge

English LanguageComputers and ElectronicsAdministrativeMathematicsCustomer and Personal Service

Abilities

Oral ComprehensionWritten ComprehensionOral ExpressionWritten ExpressionInformation OrderingDeductive ReasoningNear VisionInductive ReasoningSpeech ClarityProblem Sensitivity

Tasks

  • Design and create special programs for tasks such as statistical analysis and data entry and cleanin
  • Provide assistance with the preparation of project-related reports, manuscripts, and presentations.
  • Prepare tables, graphs, fact sheets, and written reports summarizing research results.
  • Write grant proposals.

Technology

Graphics or photo imaging softwareDesktop publishing softwareComputer based training softwareObject or component oriented development softwareData base user interface and query software

Tools

Computer data input scannersComputer laser printersDesktop computersMulti-line telephone systemsPersonal computersPhotocopying equipmentTablet computersTranscription equipment

Work Values

IndependenceAchievementWorking ConditionsRelationshipsRecognitionSupport
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: medium19-4061.00Social Science Research Assistantstitle_inference———
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

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

  • Data entry tasks — execute accurately and consistently under direct supervision in a structured research project environment.
  • Existing database records — verify for accuracy and flag apparent errors for review by a senior researcher in a university or policy research setting.
  • Statistical software packages — operate using provided scripts to run basic descriptive analyses on cleaned social science datasets.
  • Research results — compile into draft summary tables and graphs following established templates under close guidance from project leadership.
  • Project-related manuscripts and presentations — gather source materials and format reference sections in compliance with style guidelines specified by supervising researchers.
  • Structured data files — import, sort, and filter using spreadsheet software to support ongoing research project tasks.
  • Research protocols and procedural documentation — read and apply to assigned tasks, seeking clarification when ambiguities arise in a supervised team context.
  • Geographic information system tools — use at a basic level to locate and retrieve spatial datasets relevant to an assigned social science study.
  • Team meetings and research briefings — participate in attentively, taking notes and summarizing key points to support project documentation.
  • Quality control checklists — apply to completed data entry batches, identifying discrepancies and escalating unresolved issues to a supervising researcher.

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

Auto-populated·from Scorecard + DOL
Completion Rate
99%
Placement Rate
99%