AI Testing & Automation Online Live Class by Experts
Our Training/Internship Process
AI Testing & Automation - Syllabus, Fees & Duration
Introduction to AI Testing
- Software Testing Fundamentals
- Introduction to AI in Software Testing
- AI-Assisted Testing Workflow
- Benefits and Limitations of AI Testing
AI Test Case Generation
- Requirement Analysis with AI
- AI-Based Test Case Generation
- Test Scenario Creation
- Positive and Negative Test Cases
- Test Case Optimization
Prompt Engineering for Testers
- Prompt Engineering Fundamentals
- Writing Testing Prompts
- Prompts for Test Case Generation
- Prompts for Bug Analysis
AI-Assisted Test Automation
- Introduction to Test Automation
- AI-Assisted Test Script Generation
- Automated Test Maintenance
- Self-Healing Test Concepts
- AI-Based Test Optimization
Web Application Testing
- Functional Testing
- UI Testing with AI
- Regression Testing
- Cross-Browser Testing
- Automated Web Testing
API Testing with AI
- REST API Testing Fundamentals
- AI-Assisted API Test Generation
- API Test Automation
- Request and Response Validation
AI for Bug Detection
- AI-Assisted Bug Detection
- Error Analysis
- Root Cause Analysis
- Bug Classification and Prioritization
- AI-Generated Bug Reports
AI Test Data Generation
- Test Data Fundamentals
- Generating Test Data with AI
- Synthetic Test Data
- Test Data Validation
AI Performance Testing
- Performance Testing Fundamentals
- Load and Stress Testing
- AI-Assisted Performance Analysis
- Performance Report Generation
AI Testing in CI/CD
- Continuous Testing
- AI-Assisted CI/CD Workflows
- Automated Regression Testing
- Test Reporting and Quality Gates
Practical AI Testing Project
- Analyze Requirements Using AI
- Generate Test Scenarios and Test Cases
- Create Automated Test Scripts
- Execute Tests and Analyze Results
- Generate a Final Test Report
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 30 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
- Atlanta
- Austin
- Baltimore
- Boston
- Charleston
- Charlotte
- Chicago
- Colorado Springs
- Columbus
- Dallas
- Denver
- Detroit
- Fort Worth
- Fresno
- Honolulu
- Houston
- Indianpolis
- Jacksonville
- Kansas City
- Las Vegas
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- Lousville
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- Miami
- Milwaukee
- Minneapolis
- Nashville
- New Orleans
- New York
- Oklahoma City
- Omaha
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- Portland
- Raleigh
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- San Antonio
- San Diego
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- San Jose
- Seattle
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- Tulsa
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- Washington
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Course Highlights
Our Locations
Embark on a transformative journey in quality assurance with our cutting-edge AI Testing & Automation course in Minneapolis.
Throughout the course, you will delve into the fundamental concepts of AI and machine learning applied specifically to software testing challenges. As artificial intelligence revolutionizes every aspect of software development, the traditional approach to software testing is also undergoing a profound shift. By integrating AI into your QA processes, you will be able to significantly improve test coverage, reduce maintenance overhead, and enhance the overall quality and reliability of software products developed and tested in Minneapolis.
Our expert instructors will guide you through hands-on exercises using industry-leading AI-powered testing tools, enabling you to build robust, self-healing test automation frameworks that can adapt to rapid application changes. Stay ahead of the curve and become a valued expert in the rapidly evolving field of AI-driven quality assurance. . This comprehensive program is meticulously designed to equip QA professionals, automation engineers, and software developers in Minneapolis with the knowledge and practical skills needed to harness the power of AI for faster, smarter, and more effective software testing. Move beyond basic test automation and learn how AI can automate test case generation, optimize test execution, enhance visual testing, perform root cause analysis of defects, manage complex test data, and improve performance and security testing. 
