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AI+ Quality Assurance™

Course code: AT920

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.

445 EUR

538 EUR including VAT

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Course dates

Starting date: Upon request

Type: Self-paced

Course duration: 40 hours

Language: en

Price without VAT: 445 EUR

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Type Course
duration		 Language Price without VAT
Upon request Self-paced 40 hours en 445 EUR Register
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Course description

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

Target group

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.

Course structure

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

  1. 1.1 Overview of QA
  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

Prerequisites

Programming Skills, Basics of QA, Foundational knowledge of machine learning concepts

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Certification

50 questions, 70% passing, 90 minutes, online proctored exam

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