Implementing AI in Software Testing | AI in Test Automation

At Course Completion

This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore:

· Exploring AI

· Introduction to Machine Learning

· Introduction to Deep Learning

· Introduction to Data Science

· Artificial Intelligence (AI) in Software Testing

· Implementing AI in Test Automation

· Innovative AI Test Automation Tools for the Future

Audience Profile

This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise.

Prerequisites

While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos.

Outline

Day 1

1. Introduction to AI in Software Testing
Understand the basics and significance of AI in software testing.
• What is AI in Software Testing?
• Overview of AI-powered Testing Tools
• Advantages of AI-powered Testing
• Common Use Cases of AI in Software Testing
• Lab: Getting 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
• Use of AI in Test Data Generation
• Techniques for Test Data Generation using AI
• Advantages of AI in Test Data Generation
• Lab: 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.
• Detailed Study of Test Case Selection
• Advanced Techniques for Test Case Selection using AI
• Integrating AI with Existing Test Suites
• Case Studies of AI in Test Case Selection
• Lab: Selecting and Prioritizing Test Cases using AI

4. AI-Powered Test Execution and Monitoring
Understand how AI can automate test execution and provide real-time monitoring.
• Introduction to AI in Test Execution
• Real-time Test Monitoring with AI
• AI in Test Result Analysis and Reporting
• Lab: Executing and Monitoring Tests using 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
• Lab: 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
• Lab: 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
• AI in Security Testing: Identifying Vulnerabilities
• Case Studies: AI-Driven Performance and Security Improvements
• Lab: 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 & trends to your testing efforts
• Exploring the capabilities of OpenAI, ChatGPT, AutoGPT, etc.
• Real-world applications and case studies of cutting-edge AI tools in software testing
• Lab: Implementing a Sample Test with the Latest AI Tools (Open AI, ChatGPT, etc).