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  1. Programs
  3. Advanced Biostatistics for Genomics

Advanced Biostatistics for Genomics

National Institutes of Health (NIH)

Micro-CredentialCIP: 15.2045

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

Training on advanced biostatistical methods tailored for genomic data analysis| including machine learning and multivariate techniques.

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Program Pathways

Credentials this program stacks toward

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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

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Locations

Where this program is offered

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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 25-1022.00

Skills

MathematicsSpeakingInstructingReading ComprehensionActive ListeningCritical ThinkingLearning StrategiesMonitoring

Knowledge

MathematicsEducation and TrainingEnglish LanguageComputers and Electronics

Abilities

Mathematical ReasoningOral ExpressionNumber FacilityOral ComprehensionWritten ComprehensionDeductive ReasoningWritten ExpressionInductive ReasoningSpeech ClarityNear Vision

Tasks

  • Compile, administer, and grade examinations, or assign this work to others.
  • Evaluate and grade students' class work, assignments, and papers.
  • Prepare and deliver lectures to undergraduate or graduate students on topics such as linear algebra,
  • Hire adjunct faculty.

Technology

Computer based training softwareData base user interface and query softwareCalendar and scheduling softwareWord processing softwareAnalytical or scientific software

Tools

Carousel slide projectorsCompact digital camerasCompact disk CD playersComputer data input scannersComputer laser printersConference telephonesDesktop computersDigital calculatorsDigital video camerasDigital video disk DVD playersHandheld microphonesInteractive whiteboard controllersInteractive whiteboardsLaptop computersLaser facsimile machines

Work Values

AchievementIndependenceRecognitionWorking ConditionsRelationshipsSupport
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: medium25-1022.00Mathematical Science Teachers, Postsecondarytitle_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)

  • Undergraduate course lectures — prepare and deliver introductory presentations on topics such as calculus or linear algebra under the guidance of a supervising faculty mentor in a university classroom setting.
  • Examination materials — compile and administer assessments for lower-division mathematics courses using departmentally approved templates and rubrics under faculty supervision.
  • Student work — evaluate and grade routine homework assignments and quizzes using provided answer keys and grading guidelines in a postsecondary instructional context.
  • Course syllabi and handouts — prepare standard course materials by adapting existing departmental templates for use in an introductory undergraduate mathematics course.
  • Student attendance and grade records — maintain accurate logs using university learning management systems under the procedural guidance of senior faculty.
  • Classroom discussions — initiate and facilitate structured student exchanges on foundational mathematical concepts by following discussion protocols established by the course coordinator.
  • Office hours — maintain regularly scheduled sessions to provide academic guidance to undergraduate students in a university mathematics department.
  • Mathematical reasoning problems — apply deductive and inductive reasoning to explain standard proof techniques to students encountering formal mathematics for the first time.
  • Analytical software tools — use course-approved platforms such as MATLAB or Mathematica to demonstrate mathematical concepts during scheduled laboratory or recitation sessions.
  • Active listening and social awareness — observe student comprehension signals during lectures and adjust pacing or examples in response, under the mentorship of experienced instructors.

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