Smarter Software Testing & Test Automation with AI: Harness the Power of AI in Your Testing Workflow (TTAI2140)

Course Objectives

Learning Objectives

Working in an interactive learning environment, led by our engaging OpenAI expert you’ll:

• Understand AI's Role in Testing: You will develop a strong foundation in the basics of AI in software testing, including familiarity with leading AI-powered tools, to leverage AI for enhancing test efficiency and effectiveness.
• Generate Superior Test Data with AI: You will master the art of using AI to create comprehensive and varied test data sets, ensuring your testing is thorough and your software's performance is robust.
• Refine Testing with AI Insights: You will learn to use AI for smart test case selection and defect prediction, focusing your testing efforts where they are most needed and preemptively addressing issues to improve software quality.
• Automate Tests Efficiently with AI: You will acquire skills to integrate AI with test automation, boosting your testing speed and reducing manual effort, by understanding and applying AI in continuous testing and integration.
• Boost Performance & Security with AI: You will explore how AI can be instrumental in enhancing your software's performance and security, learning to identify and rectify potential vulnerabilities and performance issues effectively.
• Embrace Cutting-Edge AI Tools & Trends: You will stay ahead of the curve by understanding and applying the latest AI tools and trends in your testing processes, ensuring you're equipped to innovate and lead in AI-driven testing scenarios.

Need different skills or topics?  If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate.  We offer additional AI, machine learning, data science, programming, test automation and other related topics that may be blended with this course for a track that best suits your needs. Our team will collaborate with you to understand your needs and will target the course to focus on your specific learning objectives and goals.

Course Prerequisites

Audience

This intermediate-level course is great for experienced software testers, QA analysts, test automation engineers, and developers seeking to expand their skill set by incorporating AI-driven testing techniques. Project managers and team leads looking to improve their team's testing efficiency and effectiveness will also benefit from attending.

Attendees should be comfortable with Python or Java scripting basics for some of the hands-on labs. Non-developers are welcome to follow along with the labs or cut and paste. You should also have some familiarity with the concept of applying AI in business applications. This course does not cover AI essentials.

Course Agenda

Course Topics / Agenda

Day 1

1. Introduction to AI in Software Testing

Understand the basics and significance of AI in software testing.

• Getting Started with AI in Software Testing
• Advantages of AI-powered Testing
• Exploring AI-powered Testing Tools
• AI Testing Tools for Less Technical Testers
• Quick Guide: Top Ten Tips to Integrating AI-Powered Testing

• Additional Insights for Getting Started with AI-Powered Testing

• Common Use Cases of AI in Software Testing: Technical & Business Users
• Activity: Get familiar with the AI Testing Environment

2. Test Data Generation using AI

Learn to create realistic and diverse test datasets using AI.

• Overview of Test Data Generation
• Advantages of AI in Test Data Generation
• Techniques for Test Data Generation using AI
• Step-by-Step Guide to Creating Test Data
• Tops Tips & Best Practices for Creating Test Data using AI
• Activity: Generating and Analyzing Test Data using AI

3. Advanced Test Case Selection using AI

Dive deeper into the selection of test cases using AI to optimize testing efforts.

• Quick Guide to Applying AI to Test Case Selection
• Tips for Success Using AI Tools for Test Case Selection
• Deerp Dive: Study of Test Case Selection
• Top Tips & Best Practices for Integrating Predictive Insights into Testing Workflow
• Activity: Using AI Tools for Test Case Selection and Prioritization
• Advanced Activity: Integrating AI into Test Case Selection with Python

4. AI-Powered Test Execution and Monitoring

Understand how AI can automate test execution and provide real-time monitoring.

• Exploring AI in Test Execution: Elevating the Test Platform

• Real-time Test Monitoring with AI: Unveiling Insights as They Happen
• Transforming Analysis with AI: Deepening Understanding Through Data

• Types of Useful AI-Driven Data Reports for Testers

• Activity / Option 1: Executing and Monitoring Tests using AI
• Activity / Option 2: Executing and Monitoring Tests with AI Using Pytest
• Ten Practical Tips for Enhancing Test Execution and Monitoring with AI

Day Two

5. Defect Prediction using AI

Master the techniques to predict defects using AI, enhancing software quality.

• Deep Dive into Defect Prediction
• Techniques for Defect Prediction using AI
• Preventive Measures Based on AI Predictions
• Activity: Predicting and Analyzing Defects using AI

6. Test Automation using AI

Learn advanced test automation techniques powered by AI to streamline your testing process.

• Advanced Techniques for Test Automation using AI
• Integrating AI with Existing Automation Frameworks
• AI in Continuous Testing and Integration
• Activity: Implementing an AI-Driven Automation Test Suite 
  
  7. AI in Performance and Security Testing

Explore how AI can enhance performance and security testing.

• AI in Performance Testing: Techniques and Tools
• Top Best Practices for Leveraging AI in Performance Testing
• AI in Security Testing: Identifying Vulnerabilities
• Top Best Practices for Leveraging AI in Security Testing
• Case Studies: AI-Driven Performance and Security Improvements
• Activity: Utilizing AI for Performance and Security Testing

8. Applying the Latest Tools & Trends

Get hands-on with the latest AI tools and trends to innovate your testing process.

• Applying the Latest AI Tools to your Testing Efforts
• Utilizing GPT Models in QA and Testing: An In-depth Exploration
• Sample Prompts for Testers
• Top Ten Common Pitfalls to Avoid when Applying GPT to Testing Processes
• Activity: Implementing a Sample Test with GPT
  
  Resources Addendum

Course Materials

Setup Made Simple! Learning Experience Platform (LXP)

All applicable course software, digital courseware files or course notes, labs, data sets and solutions, live coaching support channels, CodeCoach.AI anytime tutor access, and rich extended learning and post training resources are provided for you in our “easy access, single source, no install required” online Learning Experience Platform (LXP), remote lab and content environment. Access periods vary by course. We’ll collaborate with you to ensure your team is set up and ready to go well in advance of the class. Please inquire about set up details and options for your specific course of interest.