Role-Based Programme
RB0320

GitHub Copilot for Quality Management

AI-Assisted Quality Applications, CAPA Workflows & Digital Process Support

IMAGE REQUIRED
Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how GitHub Copilot can support the development and improvement of digital applications used in quality-management workflows.
  • Explore AI-assisted coding for nonconformance tracking, CAPA, audits, inspections, quality records, and reporting.
  • Translate quality-process requirements and acceptance criteria into clearer technical tasks and application changes.
  • Use Copilot to understand existing code, generate simple features, support testing, and document quality-related workflows.
  • Apply data integrity, document control, cybersecurity, human validation, and responsible AI practices.

Tools covered

GitHub CopilotCopilot ChatCode SuggestionsRepository ContextGitHub IssuesPull RequestsCode Review ConceptsTest GenerationDocumentation Support & Quality Workflow Prototyping

Who should attend

  • Quality Managers
  • Quality Assurance Professionals
  • Quality Control Professionals
  • Quality Engineers
  • Quality Systems Professionals
  • Internal Quality Auditors
  • Supplier Quality Professionals
  • Continuous Improvement Professionals
  • Process Excellence Professionals
  • Quality Analysts
  • Operational Excellence Professionals
  • Quality Digitalization Professionals
  • Quality Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of quality-management processes
  • Familiarity with nonconformances, CAPA, audits, inspections, or quality records
  • Basic awareness of software-development or digital workflow concepts is helpful
  • Ability to describe quality requirements and expected process behaviour
  • Basic familiarity with GitHub concepts is beneficial
  • No advanced programming expertise required
  • No previous GitHub Copilot experience required

TOC Modules

Concepts
  • Understanding GitHub Copilot as an AI-assisted software-development capability
  • Understanding Copilot Chat, code suggestions, repository context, and development assistance
  • Identifying quality use cases across NCR, CAPA, audits, inspections, and reporting
  • Differentiating AI-generated implementation from validated quality-system changes
Practical activities
  • Exploring GitHub Copilot within a sample quality repository
  • Asking Copilot to explain a simple quality-related feature
  • Mapping Quality Requirement → Copilot Assistance → Human Review → Outcome

Scenarios

Nonconformance to Digital CAPA Workflow

Quality Issue → GitHub Issue → Copilot-Assisted Workflow Development → NCR Record → CAPA Tracking → Testing → Quality Review → Controlled Use

Participants create or enhance a basic digital NCR and CAPA workflow while keeping root-cause confirmation, corrective-action approval, and closure under qualified quality ownership.

Audit Finding to Validated Application Change

Audit Finding → Requirement Update → GitHub Issue → Copilot-Assisted Code Change → Test Cases → Review → Quality Validation → Approved Improvement

Participants use GitHub Copilot to support a controlled quality-system improvement while maintaining formal review, traceability, testing, and human approval.

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