Test, Evaluation, Certification, and Quality Assurance for Autonomous Systems Training by Tonex
Test, Evaluation, Certification, and Quality Assurance for Autonomous Systems Training by Tonex prepares professionals to verify, validate, evaluate, certify, and sustain autonomous systems across development, production, and deployment environments. The course addresses requirements-based testing, AI-enabled autonomy validation, acceptance criteria, environmental qualification, reliability assurance, compliance planning, and scalable quality controls. Participants learn how structured test programs reduce operational uncertainty and strengthen confidence in autonomous platforms.
Autonomous systems also expand cybersecurity risk because software, sensors, data flows, control logic, and connected interfaces can be targeted. Strong test and assurance practices help identify cybersecurity weaknesses before deployment. The course emphasizes cybersecurity testing as part of safety, reliability, and production readiness.
Learning Objectives
- Understand test and evaluation requirements for autonomous systems.
- Develop production acceptance testing strategies for scalable deployment.
- Apply verification and validation methods to AI-enabled autonomy.
- Build structured test infrastructure for repeatable quality assurance.
- Assess safety, reliability, maintainability, and certification readiness.
- Evaluate cybersecurity risks affecting autonomous system performance and trust.
Audience
- Autonomous Systems Engineers
- Test and Evaluation Professionals
- Quality Assurance Managers
- Systems Engineers
- Certification and Compliance Specialists
- Production Engineering Teams
- Reliability and Safety Engineers
- Cybersecurity Professionals
- Program Managers
- Defense, aerospace, automotive, robotics, and industrial technology professionals
Course Modules
Module 1: Autonomous Test Foundations
- Autonomous system test concepts
- Operational performance expectations
- Verification versus validation
- Evaluation planning methods
- Test readiness considerations
- Quality assurance alignment
Module 2: Requirements-Based Verification
- Requirements traceability methods
- Acceptance criteria definition
- Verification matrix development
- Functional test planning
- Evidence collection practices
- Requirement closure review
Module 3: AI Autonomy Validation
- AI behavior uncertainty
- Training data concerns
- Model performance boundaries
- Edge case identification
- Decision logic assessment
- Autonomy failure modes
Module 4: Environmental Qualification Testing
- Temperature exposure testing
- Vibration and shock checks
- Electromagnetic compatibility review
- Durability test planning
- Field condition replication
- Qualification evidence management
Module 5: Cybersecurity Assurance Testing
- Threat surface identification
- Secure interface evaluation
- Data integrity checks
- Access control review
- Adversarial input testing
- Resilience under attack
Module 6: Certification Quality Pathways
- Compliance pathway planning
- Production acceptance testing
- Reliability assurance methods
- Maintainability review process
- Safety case development
- Certification evidence packages
Enroll in Test, Evaluation, Certification, and Quality Assurance for Autonomous Systems Training by Tonex to build practical skills for testing, certifying, and assuring trustworthy autonomous systems at scale.