Login

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.
Enroll Now Enquire Now
AI+ Quality Assurance™
Price: $755.00

At a Glance: Course + Exam Overview

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

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

Module 1: Introduction to Quality Assurance and AI

  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 

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

  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) 

Module 3: Test Automation with AI

  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 

Module 4: AI for Defect Prediction and Prevention

  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 

Module 5: NLP for QA

  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 

Module 6: AI for Performance Testing

  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 

Module 7: AI in Exploratory and Security Testing

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

Module 8: Continuous 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 

Module 9: Advanced QA Techniques with AI

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

Module 10: Capstone Project

Finish the course and get certified

Certificate 1

Industry Opportunities

  • AI Quality Assurance Engineer:
    AI Quality Assurance Engineer:
    Manage AI-based automation strategies to improve testing accuracy and scalability.
  • QA Automation Lead:
    QA Automation Lead:
    Manage AI-based automation strategies to improve testing accuracy and scalability.
  • NLP QA Specialist:
    NLP QA Specialist:
    Use NLP for bug triaging, test case generation, and team communication in QA.
  • Test Automation Engineer:
    Test Automation Engineer:
    Implement AI-driven test cases and integrate AI tools into CI/CD pipelines to streamline testing.
  • Defect Prediction Specialist:
    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

`

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%
Course Price: $755.00
Instructor-Led (Live Virtual/Classroom)
  • 5 days of intensive training with live demos
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners

 

Self-Paced Online
  • ~40 hours of on-demand video lessons, e-book, podcasts, and interactive labs
  • Learn anywhere, anytime, with modular quizzes to track progress

 

Purchase Self-Paced Course

Core AI Tools Covered

TensorFlow

TensorFlow

SHAP (SHapley Additive exPlanations)

SHAP (SHapley Additive exPlanations)

Amazon S3

Amazon S3

AWS SageMaker

AWS SageMaker