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AI+ Quality Assurance

AI+ Quality Assurance

$3,599.00

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
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Description

Why this certification matters

  • 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.

Course Outline:

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

 

Prerequisites

    • Programming Skills: Basic knowledge of Python and familiarity with software testing lifecycle and tools.
    • Basics of QA: Basic knowledge of Quality Assurance principles and practices.
    • Basics of AI: Foundational knowledge of machine learning concepts is beneficial but not mandatory.

Course + Exam Overview

  • Program Name: AI+ Quality Assurance™
  • Included: Instructor-led OR Self-paced course + Official exam + Digital badge
  • Duration: Instructor-Led: 5 days (live or virtual) Self-Paced: 40 hours of content
  • Prerequisites: Programming Skills, Basics of QA, Foundational knowledge of machine learning concepts
  • Exam Format: 50 questions, 70% passing, 90 minutes, online proctored exam
  • Delivery: Online labs, projects, case studies
  • Outcome: Industry-recognized credential + hands-on experience

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