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AI Data & Robotics

AI+ Quality Assurance™

  • Gain hands-on experience with AI-powered testing tools and techniques.
  • Streamline defect detection and performance testing using intelligent automation.
  • Accelerate your QA career with our comprehensive, industry-aligned exam bundle.

All prices are in NZD, ex GST (15%).

At a Glance: Course + Exam Overview

Category AI Careers & Workforce Development Program Name: AI+ Quality Assurance™
Exam Format 50 questions, 70% passing, 90 Minutes Duration:
  • Instructor-Led: 5 Days
  • Self-Paced: 40 hours of content

🤝 You’re never on your own — Parasol Concierge Support provides integration guidance and expert VA assistance so you can focus on mastering skills while we handle the setup details.

WHAT You'll Learn

QA Fundamentals

Understand the core principles of Quality Assurance (QA), including testing methodologies, tools, and processes to ensure software quality.

Manual Testing

Master manual testing techniques, including test case creation, test execution, and defect reporting to ensure software functionality meets requirements.

Automation Testing

Learn automation testing using popular tools like Selenium, Appium, and TestNG, and understand how automation enhances testing efficiency and accuracy.

Performance Testing

Gain expertise in performance testing tools like JMeter and LoadRunner, and learn how to evaluate software performance under different conditions.

CERTIFICATION Modules

  1. 1.1 Introduction to Quality Assurance (QA) and AI 
  2. 1.2 Introduction to AI in QA 
  3. 1.3 QA Metrics and KPIs 
  4. 1.4 Use of Data in QA 

  1. 2.1 AI Fundamentals 
  2. 2.2 Machine Learning Basics 
  3. 2.3 Deep Learning Overview 
  4. 2.4 Introduction to Large Language Models (LLMs) 

  1. 3.1 Test Automation Basics 
  2. 3.2 AI-Driven Test Case Generation 
  3. 3.3 Tools for AI Test Automation 
  4. 3.4 Integration into CI/CD Pipelines 

  1. 4.1 Defect Prediction Techniques 
  2. 4.2 Preventive QA Practices 
  3. 4.3 AI for Risk-Based Testing 
  4. 4.4 Case Study: Defect Reduction with AI 

  1. 5.1 Basics of NLP 
  2. 5.2 NLP in QA 
  3. 5.3 LLMs for QA 
  4. 5.4 Case Study: Using NLP for Bug Triaging 

  1. 6.1 Performance Testing Basics 
  2. 6.2 AI in Performance Testing 
  3. 6.3 Visualization of Performance Metrics 
  4. 6.4 Case Study: AI in Performance Testing of a Cloud App 

  1. 7.1 Exploratory Testing with AI 
  2. 7.2 AI in Security Testing 
  3. 7.3 Case Study: Enhancing Security Testing with AI 

  1. 8.1 Continuous Testing Overview 
  2. 8.2 AI for Regression Testing 
  3. 8.3 Use-Case: Risk-Based Continuous Testing 

  1. 9.1 AI for Predictive Analytics in QA 
  2. 9.2 AI for Edge Cases 
  3. 9.3 Future Trends in AI + QA 

Industry opportunities

AI Quality Assurance Engineer:

    Manage AI-based automation strategies to improve testing accuracy and scalability.

QA Automation Lead:

    Manage AI-based automation strategies to improve testing accuracy and scalability.

NLP QA Specialist:

    Use NLP for bug triaging, test case generation, and team communication in QA.

Test Automation Engineer:

    Implement AI-driven test cases and integrate AI tools into CI/CD pipelines to streamline testing.

Defect Prediction Specialist:

    Apply AI and machine learning to predict and prevent defects, ensuring smoother development cycles.

FREQUENTLY ASKED QUESTIONS

Yes, the course is suitable for individuals who are new to QA, as it starts with the basics and gradually builds up to more advanced concepts like AI integration into testing.

Yes, the course covers industry-standard AI tools and platforms used for test automation, defect prediction, performance testing, and more, ensuring you stay up to date

Upon completion, you will have a portfolio of hands-on projects, including the capstone project, which showcases your ability to apply AI in QA, making you highly competitive

Yes, the course includes case studies and hands-on activities involving cloud applications, helping you leverage AI for performance and scalability testing

You’ll work on projects that include defect prediction, automation of regression tests, performance testing in cloud environments, and applying AI for security testing

PREREQUISITES

  • Programming Skills: Basic knowledge of Python and familiarity with Software Testing. 
  • Basics of Quality Assurance (QA): Foundational knowledge of QA principles and practices. 
  • Basics of AI: A basic understanding of machine learning concepts is beneficial but not mandatory. 

EXAM DETAILS

Duration

90 Minutes

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

EXAM BLUEPRINT

Introduction to Quality Assurance and AI 10%
Fundamentals of AI, ML, and Deep Learning 15%
Test Automation with AI 15%
AI for Defect Prediction and Prevention 15%
NLP for QA 10%
AI for Performance Testing 10%
AI in Exploratory and Security Testing 10%
Continuous Testing with AI 5%
Advanced QA Techniques with AI 5%
Capstone Project 5%

Instructor-Led (Live Virtual/Classroom)

Instructor-Led Course 

 

🚀 Learn directly from certified AI trainers in live, interactive sessions. Get real-time guidance, practical exercises, and the accountability of a structured classroom experience. Perfect for professionals who want expert support and a clear path to certification.

At Parasol Virtual, we go beyond just certification. Our team is here to support your learning journey with guidance, resources, and local assistance to ensure you succeed. You’re not learning alone — you’re part of a global community with local support.

Request Virtual Training

Self-Paced Online

Self-Paced Course

🌐 Study anytime, anywhere with 24/7 access to course materials, practice tests, and resources. Move at your own speed while still working towards globally recognized certification. Designed for busy learners who value flexibility without compromising quality.

 

At Parasol Virtual, we go beyond just certification. Our team is here to support your learning journey with guidance, resources, and local assistance to ensure you succeed. You’re not learning alone — you’re part of a global community with local support.

 

 

 

 

Purchase Self-Paced Course

TECHNOLOGIES USED

TensorFlow
TensorFlow
SHAP (SHapley Additive exPlanations)
SHAP (SHapley Additive exPlanations)
Amazon S3
Amazon S3
AWS SageMaker
AWS SageMaker