Detail kurzu

AI+ Quality Assurance

EDU Trainings s.r.o.

Popis kurzu

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

Price of the certification exam is included in the price of the course. Unlock Advanced QA Skills with AI:
Integrate AI and machine learning into testing to automate tasks, predict defects, and optimize performance.
Enhance Testing Efficiency and Accuracy:
Use AI tools to speed up defect detection, improve software quality, and reduce manual errors.
Stay Ahead in a Competitive Market:
Equip yourself with in-demand AI skills to meet industry standards and stand out in software testing.
Future-Proof Your Career:
Master AI technologies like NLP and defect prediction, positioning yourself for future growth in QA.
Real-World Application and Hands-On Experience:
Gain practical experience in AI techniques, preparing you to tackle complex QA challenges and improve software quality.

TensorFlow
SHAP (SHapley Additive exPlanations)
Amazon S3
AWS SageMaker

Obsah kurzu

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

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

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

2.1 AI Fundamentals
2.2 Machine Learning Basics
2.3 Deep Learning Overview
2.4 Introduction to Large Language Models (LLMs)

Module 3: Test Automation with AI

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

Module 4: AI for Defect Prediction and Prevention

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

Module 5: NLP for QA

5.1 Basics of NLP
5.2 NLP in QA
5.3 LLMs for QA
5.4 Case Study: Using NLP for Bug Triaging

Module 6: AI for Performance Testing

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

Module 7: AI in Exploratory and Security Testing

7.1 Exploratory Testing with AI
7.2 AI in Security Testing
7.3 Case Study: Enhancing Security Testing with AI

Module 8: Continuous Testing with AI

8.1 Continuous Testing Overview
8.2 AI for Regression Testing
8.3 Use-Case: Risk-Based Continuous Testing

Module 9: Advanced QA Techniques with AI

9.1 AI for Predictive Analytics in QA
9.2 AI for Edge Cases
9.3 Future Trends in AI + QA

Module 10: Capstone Project

Cieľová skupina

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.
Certifikát Na dotaz.
Hodnotenie




Organizátor