Test AI assisted testing tools
- Duration: 7 hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
9000+ Professionals Enrolled
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Course Overview
The AI-Assisted Testing Tools (Test.ai / TestGrid / LambdaTest with AI) course equips QA and engineering teams with hands-on skills to modernise testing using AI-enabled capabilities like self-healing tests, smart element detection, codeless automation, and analytics-driven quality insights. Learners practice building reliable automated tests, running them across browsers and devices, and integrating results into CI/CD pipelines for continuous quality.The course focuses on operational outcomes: fewer flaky tests, reduced maintenance, faster regression cycles, and clearer release readiness—so teams ship with confidence, not crossed fingers.
Course Details
- Understand how AI improves test automation reliability (self-healing, smart locators, anomaly detection)
- Create automation faster using codeless/low-code workflows where appropriate
- Reduce flaky failures through stabilisation patterns, retries, and root-cause triage workflows
- Scale execution across browsers/devices with cloud testing and parallel runs
- Improve defect detection with visual validation and intelligent assertions
- Operationalise QA with CI/CD integrations, reporting dashboards, and governance practices
- Beginner-friendly: no prior AI experience required
- Helpful (not mandatory): familiarity with QA fundamentals (test cases, regression testing, bug lifecycle)
- Helpful (not mandatory): exposure to automation basics (selectors, assertions, basic scripting, CI/CD concepts)
- Best suited for QA engineers, SDETs, developers, QA leads, product teams, and DevOps/release teams
- Explain AI-assisted testing concepts (self-healing, smart discovery, prioritisation, analytics)
- Build automated tests using AI-enabled/codeless/low-code approaches
- Improve test stability using flake control and resilient locator strategies
- Run tests at scale across browsers/devices and interpret results effectively
- Integrate automated testing into CI/CD pipelines with actionable reporting
- Establish a practical governance model (test ownership, review gates, release readiness signals)
- AI-assisted testing landscape: where AI helps and what still needs human judgement
- Test design for automation: stable assertions, maintainable flows, and reusable components
- Codeless/low-code automation workflows: faster creation with guardrails
- Self-healing tests: locator resilience, UI change tolerance, and maintenance reduction
- Cross-browser/device execution: parallel runs, environment management, and reliability controls
- Visual & functional validation: catching UI regressions and behavioural issues
- Flaky test management: stabilisation patterns, retries, quarantines, and root-cause workflows
- CI/CD integration: triggers, pipelines, gates, and reporting for release readiness
- Reporting & analytics: trends, failure clustering, and quality signals that matter
- Governance & best practices: standards, ownership, access control, and responsible adoption
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