AI+ Quality Assurance Practitioner™ eLearning
Master AI-Driven Quality Assurance: Elevate Your Testing Efficiency, Accuracy, and Scalability
- AI Testing Mastery: Gain hands-on experience with AI-powered testing tools and techniques
- Intelligent Automation Edge: Streamline defect detection and performance testing using intelligent automation
- QA Career Fast-Track: Accelerate your QA career with our comprehensive, industry-aligned exam bundle
Duur: 5 dag(en)
- QA Professionals: Looking to enhance their testing strategies with AI-driven tools and techniques.
- Software Testers: Eager to improve defect detection and automate their testing processes.
- Developers: Interested in integrating AI into the software development lifecycle for better testing efficiency.
- Data Scientists: Wanting to apply AI and machine learning principles to software quality assurance.
- Tech Managers: Seeking to stay ahead of industry trends and lead teams in AI-enhanced QA practices.
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Unlock Advanced QA Skills with AI:
Integrate AI and machine learning into testing to automate tasks, predict defects, and optimize performance.
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Enhance Testing Efficiency and Accuracy:
Use AI tools to speed up defect detection, improve software quality, and reduce manual errors.
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Stay Ahead in a Competitive Market:
Equip yourself with in-demand AI skills to meet industry standards and stand out in software testing.
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Future-Proof Your Career:
Master AI technologies like NLP and defect prediction, positioning yourself for future growth in QA.
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Real-World Application and Hands-On Experience:
Gain practical experience in AI techniques, preparing you to tackle complex QA challenges and improve software quality.
Inhoud
- 1.1 Overview of QA
- 1.2 Introduction to AI in QA
- 1.3 QA Metrics and KPIs
- 1.4 Use of Data in QA
- 2.1 AI Fundamentals
- 2.2 Machine Learning Basics
- 2.3 Deep Learning Overview
- 2.4 Introduction to Large Language Models (LLMs)
- 3.1 Test Automation Basics
- 3.2 AI-Driven Test Case Generation
- 3.3 Tools for AI Test Automation
- 3.4 Integration into CI/CD Pipelines
- 4.1 Defect Prediction Techniques
- 4.2 Preventive QA Practices
- 4.3 AI for Risk-Based Testing
- 4.4 Case Study: Defect Reduction with AI
- 5.1 Basics of NLP
- 5.2 NLP in QA
- 5.3 LLMs for QA
- 5.4 Case Study: Using NLP for Bug Triaging
- 6.1 Performance Testing Basics
- 6.2 AI in Performance Testing
- 6.3 Visualization of Performance Metrics
- 6.4 Case Study: AI in Performance Testing of a Cloud App
- 7.1 Exploratory Testing with AI
- 7.2 AI in Security Testing
- 7.3 Case Study: Enhancing Security Testing with AI
- 8.1 Continuous Testing Overview
- 8.2 AI for Regression Testing
- 8.3 Use-Case: Risk-Based Continuous Testing
- 9.1 AI for Predictive Analytics in QA
- 9.2 AI for Edge Cases
- 9.3 Future Trends in AI + QA
- TensorFlow
- SHAP (SHapley Additive exPlanations)
- Amazon S3
- AWS SageMaker
Lesmethode
Instructor-led OR Self-paced course + Official exam + Digital badge
Kenmerken
Online proctored exam included, with one free retake.
Exam format:
50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Voorkennis
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Programming Skills, Basics of QA, Foundational knowledge of machine learning concepts

