- AI Certifications
AI+ Quality Assurance™
This globally recognized AI+ Quality Assurance (QA)™ Certification Course by AI CERTs® equips professionals with essential knowledge to apply artificial intelligence in software testing, quality assurance, and validation—enabling them to confidently begin their journey into AI-driven QA, test automation, and intelligent quality engineering.
AI+ Quality Assurance™ Certification
Synergogy, the Authorized Training Partner (ATP) of AI Certs, brings you the AI Foundation Course designed to help learners understand the fundamentals of Artificial Intelligence. This globally recognized AI+ Quality Assurance (QA)™ Certification Course by AI CERTs® equips professionals with essential knowledge to apply artificial intelligence in software testing, quality assurance, and validation enabling them to confidently begin their journey into AI-driven QA, test automation, and intelligent quality engineering.
- Format: Self paced online course.
- Level: Gain hands-on experience with AI-powered testing tools and techniques
- Certificate: AI+ Quality Assurance™ Certification by AI Certs®.
- Partner: Delivered by Synergogy as an ATP for AI Certs.
AI+ Quality Assurance™ Certification
This course includes
- Online Self-Paced Learning
- Online Proctored Exam with 1 Free Retake
- Digital Badge
- High-Quality Videos, E-books, and Podcasts
- Access for Tablet & Phone
- Capstone Projects
- Case Studies
- Quizzes & Assessments
- AI Mentor for Personalized Guidance
Why This Certification Matters
Building Advanced AI-Driven QA Expertise
Learn how to apply artificial intelligence and machine learning within quality assurance to automate testing workflows, anticipate defects, and improve system performance.
Improving Testing Speed and Reliability
Leverage AI-powered tools to accelerate defect identification, enhance test accuracy, and minimize reliance on error-prone manual testing processes.
Remaining Competitive in Modern Software Testing
Develop in-demand AI-enabled QA skills that align with evolving industry standards and help you stand out in today’s competitive software testing landscape.
Preparing for the Future of Quality Engineering
Gain hands-on experience with AI technologies such as natural language processing and predictive defect analysis, positioning yourself for long-term career growth in QA.
Applying AI Techniques to Real QA Challenges
Build practical expertise through real-world applications of AI in quality assurance, enabling you to address complex testing challenges and deliver higher-quality software.
Quality Assurance Professionals:
Strengthen testing methodologies by adopting AI-powered tools and intelligent quality engineering practices.
Software Testing Specialists:
Enhance defect detection capabilities and automate testing workflows using AI-driven techniques.
Software Developers:
Learn how to embed AI into the software development lifecycle to improve test coverage, efficiency, and overall product quality.
Data Scientists and AI Practitioners:
Apply machine learning and AI concepts to software quality assurance, defect prediction, and test optimization.
Technology and QA Managers:
Stay ahead of industry trends by leading teams through the adoption of AI-enhanced QA strategies and modern testing frameworks.
- TensorFlow
- SHAP (SHapley Additive exPlanations)
- Amazon S3
- AWS SageMaker
- 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.
- Introduction to Quality Assurance (QA) and AI – 7%
- Fundamentals of AI, ML, and Deep Learning – 9%
- Test Automation with AI – 9%
- AI for Defect Prediction and Prevention – 9%
- NLP for QA – 9%
- AI for Performance Testing – 12%
- AI in Exploratory and Security Testing – 12%
- Continuous Testing with AI – 12%
- Advanced QA Technique With AI – 12%
- Capstone Project – 9%
What You'll Learn
1: Introduction to Quality Assurance (QA) and AI
Core principles of Quality Assurance and testing methodologies
Evolution of QA in modern software development
How AI transforms traditional QA processes
QA metrics, KPIs, and data-driven quality measurement
2: Fundamentals of AI, Machine Learning, and Deep Learning
Foundations of artificial intelligence and intelligent systems
Supervised, unsupervised, and reinforcement learning
Deep learning and neural networks for QA use cases
Role of Large Language Models (LLMs) in quality engineering
3: AI-Driven Test Automation
Test automation fundamentals and frameworks
AI-powered test case generation and maintenance
Intelligent regression testing
Integrating AI-based testing into CI/CD pipelines
4: AI for Defect Prediction and Preventive QA
Machine learning techniques for defect prediction
Risk-based testing and prioritization using AI
Preventive QA strategies and early defect detection
Continuous monitoring and quality optimization
5: Natural Language Processing (NLP) for QA
NLP fundamentals for QA applications
Automated bug triaging and defect classification
Test scenario generation using NLP
Leveraging LLMs (e.g., GPT, BERT) for QA analysis and reporting
6: AI for Performance and Scalability Testing
Performance testing concepts and methodologies
AI-driven performance analytics and bottleneck detection
Predictive load testing and resource optimization
Visualization of performance metrics and dashboards
7: AI in Exploratory, Security, and Advanced Testing
AI-powered exploratory testing and edge-case discovery
Security testing using AI for vulnerability and threat detection
Adversarial testing and anomaly detection
Advanced QA techniques integrating emerging technologies
8: Continuous Testing and Capstone Project
Continuous testing in Agile and DevOps environments
AI-enabled regression and risk-based continuous testing
End-to-end AI-driven QA solution design
Capstone project applying AI to real-world QA challenges
Bring our
AI+ Foundation™ Course in-house
Interested in getting your team started with the AI Foundation Course, fully customised for your team?
FAQs - AI+ Quality Assurance™
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What is the AI+ Quality Assurance (QA)™ Certification?
The AI+ Quality Assurance (QA)™ Certification by AI CERTs® is a globally recognized program that trains professionals to apply artificial intelligence and machine learning techniques to software testing, quality assurance, and intelligent test automation.
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Who should enroll in the AI+ Quality Assurance (QA)™ course?
This certification is ideal for QA professionals, software testers, developers, data scientists, QA managers, and technology leaders who want to enhance testing efficiency, accuracy, and software quality using AI-driven approaches.
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What skills will I gain from the AI+ Quality Assurance (QA)™ Certification?
Learners gain practical skills in AI-driven test automation, defect prediction, NLP-based test analysis, performance and security testing with AI, continuous testing in CI/CD pipelines, and intelligent quality engineering practices.
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Are there any prerequisites for enrolling in the AI+ Quality Assurance (QA)™ Certification?
No formal prerequisites are required. However, basic knowledge of software testing concepts, SDLC, or programming fundamentals can help learners better understand AI-powered QA techniques.
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How does the AI+ Quality Assurance (QA)™ Certification support career growth?
The certification validates in-demand AI-enabled QA skills, preparing professionals for roles such as AI QA Engineer, Test Automation Engineer, Quality Engineer, QA Lead, and QA Manager in modern software development environments.
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