AI+ Quality Assurance™
AT- 920
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
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Job Roles & Industry Outlook
AI Specialist
Apply AI technologies to solve business problems and drive innovation across industries.
Business Analyst
Analyze business processes and leverage AI to optimize operations and decision-making.
Data Analyst
Transform data into actionable insights using AI-powered analytics tools.
Technology Consultant
Guide organizations in adopting AI solutions aligned with their strategic goals.
Innovation Manager
Lead AI-driven innovation initiatives to enhance organizational capabilities.
Industry Growth: AI+ Quality Assurance™
- 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.
Who Should Enroll?
- 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.
What You'll Learn
- 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
- 2.1 AI Fundamentals
- 2.2 Machine Learning Basics
- 2.3 Deep Learning Overview
- 2.4 Introduction to Large Language Models (LLMs)
- 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
- 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
- 5.1 Basics of NLP
- 5.2 NLP in QA
- 5.3 LLMs for QA
- 5.4 Case Study: Using NLP for Bug Triaging
- 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
- 7.1 Exploratory Testing with AI
- 7.2 AI in Security Testing
- 7.3 Case Study: Enhancing Security Testing with AI
- 8.1 Continuous Testing Overview
- 8.2 AI for Regression Testing
- 8.3 Use-Case: Risk-Based Continuous Testing
- 9.1 AI for Predictive Analytics in QA
- 9.2 AI for Edge Cases
- 9.3 Future Trends in AI + QA
Tools You'll Explore
TensorFlow
SHAP (SHapley Additive exPlanations)
Amazon S3
AWS SageMaker
Prerequisites
- Programming Skills, Basics of QA, Foundational knowledge of machine learning concepts
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via AI proctored exam platform (flexible scheduling)
Exam Blueprint
- Module 1: Introduction to Quality Assurance (QA) and AI - 10%
- Module 2: Fundamentals of AI, ML, and Deep Learning - 10%
- Module 3: Test Automation with AI - 10%
- Module 4: AI for Defect Prediction and Prevention - 10%
- Module 5: NLP for QA - 10%
- Module 6: AI for Performance Testing - 10%
- Module 7: AI in Exploratory and Security Testing - 10%
- Module 8: Continuous Testing with AI - 10%
- Module 9: Advanced QA Techniques with AI - 10%
- Module 10: Capstone Project - 10%
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Frequently Asked Questions
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.
This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.
The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.