Instructor-Led | Virtual or In-Person | 1 Full or 2 Half-Days | 25 Participants → AI & ML

AI-Driven Test Automation (002)


Description
AI has been rapidly changing the way we approach software testing. Traditional test automation is time-consuming to create and breaks down easily in the presence of change. Thankfully, AI is helping testing teams create less procedural, more resilient tests that can self-heal in the presence of modern, rapidly changing, highly dynamic production systems. This sounds great, but you may be asking yourself: How do I get started? What additional skills do I need to learn? What tools are available for me to start using, right now? Join us as we break down different AI techniques and apply them to different testing problems. Discover freely available AI-driven test automation tooling that will help you start building AI-first test automation today without writing a single line of code. Want to tackle the hardest of challenges, and want to learn how to generate new test cases? We will also cover open source tools that can help you build your neural networks for tackling tough testing problems. Let's build and execute real AI-first tests. No prior programming or AI/ML experience is needed!
Content
  • Course Introduction
  • Introductions
  • Course Goals
  • AI and Machine Learning
  • Definitions
  • Categories of ML
  • ML Models and Algorithms
  • Artificial Neural Networks
  • Hands-On: The Teachable Machine
  • How Neural Networks Learn
  • Tensorflow Playground
  • AI-Driven Test Automation By Level
  • AI for UI Testing
  • AI Element Detection
  • Hands-On: UI Element Localization and OCR
  • RL-Based Application Navigation
  • Hands-On: UI Test Automation
  • AI for API Testing
  • AI for Unit Testing
  • Hands-On: Unit Test Automation
  • AI-Driven Test Automation By Attribute
  • AI for User Design Testing
  • AI for Accessibility Testing
  • AI for Performance Testing
  • AI for Security Testing
  • AI-Driven Test Automation By Domain
  • AI for Game Testing
  • AI for Video Quality Testing
  • AI for Digital Avatar Testing
  • Optional Advanced/Special Topics
  • Decision Tree Learning for UI Element Classification
  • Diagnosing Test Flakiness using Bayesian Network Learning
  • Towards Testing the Metaverse and Beyond with AI
  • Wrap Up
  • Lessons Learned
  • Future Directions
Completion rules
  • All units must be completed