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AI Powered Testing
Home
Courses
AI Powered Testing
Home
Courses
AI Powered Testing
Curriculum
6 Sections
45 Lessons
10 Weeks
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Module 1: Introduction to AI for Software Testing
8
1.1
Introduction to Artificial Intelligence
1.2
Machine Learning vs AI vs Generative AI
1.3
Large Language Models (LLMs)
1.4
Generative AI fundamentals
1.5
Role of AI in Software Testing
1.6
Traditional Testing vs AI-Assisted Testing
1.7
Benefits and challenges of AI in QA
1.8
AI Testing lifecycle
Module 2: Generative AI Fundamentals for Testers
7
2.1
Understanding Large Language Models
2.2
Prompts and prompt engineering
2.3
Writing effective prompts for testing
2.4
Context and instructions
2.5
Improving AI-generated responses
2.6
Common AI limitations and hallucinations
2.7
Responsible use of AI in software testing
Module 3: AI-Assisted Test Case Design
9
3.1
Generate test scenarios using AI
3.2
Generate positive and negative test cases
3.3
Boundary-value test cases
3.4
Edge-case identification
3.5
Functional test case generation
3.6
Regression test case generation
3.7
Risk-based test case generation
3.8
Test case optimization
3.9
Identifying missing test scenarios using Ai
Module 4: AI-Assisted Test Automation
7
4.1
Introduction to AI-assisted automation
4.2
Generate automation scripts using AI
4.3
Convert manual test cases into automation scripts
4.4
Generate Selenium code using AI
4.5
Debug automation scripts using AI
4.6
Optimize existing automation scripts
4.7
AI-assisted Page Object Model implementation
Module 5: AI for Test Data Generation
7
5.1
Test data requirements
5.2
Generate realistic test data
5.3
Positive and negative test data
5.4
Boundary test data
5.5
Synthetic test data
5.6
Masking and protecting sensitive data
5.7
Data validation using AI
Module 6: AI in CI/CD and DevOps Testing
7
6.1
AI in CI/CD pipelines
6.2
AI-assisted Jenkins workflows
6.3
Automated test analysis
6.4
Test failure analysis
6.5
Regression test optimization
6.6
Test result summarization
6.7
Continuous Testing with AI
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