AI+ Quality Assurance Practitioner™
- From 505 EUR + VAT
- Self-paced online Start anytime
- Duration 40 hours of content, self-paced
- Language English
- Prerequisite Programming Skills, Basics of QA, Foundational knowledge of machine learning concepts
- Topic AI Data & Robotics
Overview
What the course covers
The course, the materials and the exam are in English. The description below is the original AI CERTs® text.
- 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
Prerequisites
Programming Skills, Basics of QA, Foundational knowledge of machine learning concepts
Audience
Who is it for
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.
In the price
What the price includes
- Self-paced online course with the full learning material
- The official AI CERTs® exam
- Digital badge after passing the exam
Course content
Syllabus
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
Exam
About the exam
- 50 Questions
- 90 min Time limit
- 70% Pass mark
- Online proctored exam
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