Master AI-driven testing workflows: learn practical GenAI tools and build agentic, multi-agent automation pipelines that generate tests, triage defects, produce test data, and orchestrate end-to-end testing tasks. Hands-on agent templates, prompts, and production-ready examples to make AI a productive part of your testing toolkit.

What this Bundle covers:

This bundle combines two complementary courses to make you an AI-powered testing practitioner. Start with GenAI Tools & AI Agents for Software Testing to understand how to use LLMs and agent frameworks to generate test cases, create test data, assist with debugging, and integrate AI into existing test frameworks. Continue with Agentic AI — Build Multi-Agent Automation Workflows to design, implement, and orchestrate multiple specialized agents (e.g., test-generator, runner, validator, triage-agent) that collaborate to automate complex testing workflows. Each course includes hands-on labs, reusable agent blueprints, prompt libraries, and best practices for safe, reliable automation so you can apply these techniques immediately.

What I will Learn:

• GenAI Tools & AI Agents for Software Testing:
  
  
• Overview of GenAI for testing: model selection, prompt design, and output validation
  
  
• Automated test-case and test-data generation using LLMs
  
  
• Creating single-purpose agents for spec-to-test conversion, exploratory testing assistance, and test maintenance
  
  
• Integrating LLM outputs with test frameworks and version control
  
  
• Safety and quality controls: validation, guardrails, hallucination mitigation, and reproducibility strategies
  
  
• Practical examples: auto-generated unit/integration tests, defect reproduction steps, and CI hooks for AI-assisted tasks
  
  
  
• Agentic AI — Build Multi-Agent Automation Workflows:
  
  
• Principles of agentic systems: roles, communication patterns, task decomposition, and orchestration
  
  
• Designing multi-agent pipelines for testing: generator, executor, validator, reporter, and remediation agents
  
  
• Implementing agents with popular frameworks and SDKs, including connector patterns for toolchains (CI, issue trackers, test runners)
  
  
• Coordination strategies: message passing, queues, retries, and conflict resolution
  
  
• Monitoring, observability, and governance: logs, metrics, human-in-the-loop checkpoints, and access controls
  
  
• Case studies: auto-regression triage, prioritized test selection, and continuous test-suite upkeep using agents
  
  
• Practical deliverables:
  
  
• Agent blueprints and starter repos for common testing tasks
  
  
• Prompt library and prompt-engineering templates for reproducible outputs
  
  
• Example integration scripts to connect agents with CI pipelines, test runners, and issue trackers
  
  
• Test-validation templates, safety checklists, and governance guidelines
  
  

Downloadable assets and practice material: starter agent repositories, prompt templates, sample multi-agent workflows, CI integration examples, and hands-on lab exercises with solutions.

Become an AI-powered tester and automation architect: apply GenAI to generate high-quality tests and build coordinated multi-agent systems that scale testing efforts, reduce manual effort, and improve productivity. Practical code, agent designs, and governance patterns — everything needed to move from exploration to production-grade AI testing workflows.