Sunday, September 22, 2024 - 8:30am to Monday, September 23, 2024 - 5:00pm

AI for Testers

Artificial Intelligence (AI) has taken the world by storm, increasing the productivity of workers in a wide range of industries, especially software. But, it’s also understandably led to uncertainty and fear about the personal and implications for disciplines such as software testing.

If you’re interested in cutting through the hype and understanding how AI affects the testing profession, then this course is for you. In this hands-on class, you will learn how to test systems with AI components and how to apply AI to the process of testing itself.

Key takeaways from this class include:

  • Learn how to effectively test and validate AI model input data and datasets.
  • Understand how to effectively test AI models during model development and training.
  • Apply effective testing techniques to software systems that include AI models.
  • Learning how to leverage AI to support test case and script generation.
  • Understand how to leverage AI to support test planning and management.

Who Should Attend
This course is ideal for those who test AI-based systems or wish to use AI to support their current software testing activities. This includes those in hands-on testing roles or test managers, as well as software developers and development managers.

Laptop and RDP Required
This class involves hands-on activities using sample software to better facilitate learning. Each student should bring a laptop with a remote desktop protocol (RDP) client pre-installed. Connection specifics and credentials will be supplied during class. Please work with your IT Admin before class to verify that your RDP client can be used to access a virtual machine running in the Amazon Web Services (AWS) environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.

Course Outline

Session 1: Introduction to AI/ML and AI for Testers

  • Definition of AI and AI effect
  • AI-based and conventional systems
  • Types of AI
  • Introduction to machine learning and neural networks
  • Generative AI and LLMs
  • Introduction to AI for Testing
  • Example AI-based system

Session 2: Testing AI Models and their Data

  • Machine learning process
  • Testing input data
  • Testing AI model data pipelines
  • Testing AI models
  • Testing AI model training pipelines
  • Demos and Hands-on Exercises

Session 3: Testing AI-based Systems

  • End-to-end AI-based system process
  • Model testing and delivery options
  • AI-based systems testing process
  • Component integration testing
  • System testing
  • Acceptance testing
  • Model monitoring
  • Model retraining
  • Demos and Hands-on Exercises

Session 4: AI-Assisted Test Planning and Management

  • AI-based testing process
  • Prompt engineering for testers
  • AI in test planning & documentation
  • AI for defect management
  • Using AI to generate and transform test data
  • Demos and Hands-on Exercises

Session 5: AI-Assisted Testing

  • How AI helps testing
  • AI capabilities that support test automation
  • AI-based test script generation
  • AI-assisted UI testing
  • Using AI to optimize regression test suites
  • Demos and Hands-on Exercises

Session 6: Wrapup

  • Aha moments
  • References
  • Course survey
  • Next steps and additional information

Class Daily Schedule

Sign-In/Registration 7:30 - 8:30 a.m.
Morning Session 8:30 a.m. - 12:00 p.m.
Lunch 12:00 - 1:00 p.m.
Afternoon Session 1:00 - 5:00 p.m.
Times represent the typical daily schedule. Please confirm your schedule at registration.

Training Course Fee Includes

• Digital course materials
• Continental breakfasts and refreshment breaks
• Lunches

Jonathan Kauffman
Coveros, Inc.

Jonathan Kauffman works as an agile software development and test consultant at Coveros, a company that helps organizations develop secure software using agile methods. In this role, Jonathan has helped both government and commercial organizations develop and test high-quality applications, and he has gained his experience by working with health care, biomedical device, and research organizations. Jonathan also presents at and attends Meetups to help maintain his connection with the software testing community and to stay abreast of recent industry developments. Before joining Coveros, he earned his B.S. in computer science from Allegheny College, where he published research on techniques for optimizing regression test suites.

Tom-Stiehm
Coveros

Tom Stiehm has been developing applications and managing software development teams for over twenty years. As CTO of Coveros, he is responsible for the oversight of all technical projects and integrating new technologies and testing practices into software development projects. Recently, Tom has been focusing on how to incorporate DevSecOps and agile best practices into projects and how to achieve a balance between team productivity and cost while mitigating project risks. One of the best risk mitigation techniques Tom has found is leveraging DevSecOps and agile testing practices into all aspects of projects. Previously, as a managing architect at Digital Focus, Thomas was involved in agile development and found that agile is the only methodology that makes the business reality of constant change central to the process.