AI+ Quality Assurance

Course subjects

Module 1: Introduction to Quality Assurance (QA) and AI

• Overview of QA

• Introduction to AI in QA

• QA Metrics and KPIs

• Use of Data in QA

Module 2: Fundamentals of AI, ML, and Deep Learning

• AI Fundamentals

• Machine Learning Basics

• Deep Learning Overview

• Introduction to Large Language Models (LLMs)

Module 3: Test Automation with AI

• Test Automation Basics

• AI-Driven Test Case Generation

• Tools for AI Test Automation

• Integration into CI/CD Pipelines

Module 4: AI for Defect Prediction and Prevention

• Defect Prediction Techniques

• Preventive QA Practices

• AI for Risk-Based Testing

• Case Study: Defect Reduction with AI

Module 5: NLP for QA

• Basics of NLP

• NLP in QA

• LLMs for QA

• Case Study: Using NLP for Bug Triaging

Module 6: AI for Performance Testing

• Performance Testing Basics

• AI in Performance Testing

• Visualisation of Performance Metrics

• Case Study: AI in Performance Testing of a Cloud App

Module 7: AI in Exploratory and Security Testing

• Exploratory Testing with AI

• AI in Security Testing

• Case Study: Enhancing Security Testing with AI

Module 8: Continuous Testing with AI

• Continuous Testing Overview

• AI for Regression Testing

• Use-Case: Risk-Based Continuous Testing

Module 9: Advanced QA Techniques with AI

• AI for Predictive Analytics in QA

• AI for Edge Cases

• Future Trends in AI + QA

Module 10: Capstone Project