AICERTS, Artificial Intelligence

AI+ Quality Assurance™

Instructor

Falandile Ntshangase

0 reviews

Course details

Lectures : 33

Description
FAQ
Reviews

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.

At a Glance: Course + Exam Overview

Program Name

AI+ Quality Assurance™

Included

Instructor-led OR Self-paced course + Official exam + Digital badge

Duration

Instructor-Led: 5 day (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

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.

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 Details

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

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%

Can i take the course if i'm new to quality assurance?

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.

Will this course cover AI tools used in the industry?

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

How will i be able to demonstrate the skills i have Learned in this course to employers?

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

Will the course prepare me for working with Cloud-based testing enviroments?

Yes, the course includes case studies and hands-on activities involving cloud applications, helping you leverage AI for performance and scalability testing

What kind of real-world projects will i work on in this course?

You’ll work on projects that include defect prediction, automation of regression tests, performance testing in cloud environments, and applying AI for security testing

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