Everything You Need to Become an AI Tester

Name: Everything You Need to Become an AI Tester
Rating: 4.0 (36 reviews)

ISTQB AI Test Certification Prep

Created byAdine Sikandeer

Last updated 7/2025

English

English [Auto],

What you'll learn

Understand the current state and expected trends of AI
Experience the implementation and testing of a ML model and recognize where testers can best influence its quality
Design and execute test cases for AI-based systems
Understand how AI can be used to support software testing
Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities

Course content

11 sections • 33 lectures • 1h 30m total length

Introduction to whole course1:41
Introduction to AI and AI Effect1:48
AI Categories2:38
How AI Different from regular computer systems?3:23
AI Technologies0:57
Please check out AI Technologies, each technolgy has it's own logic. You don't need to remember all, just need to know there's different types of logic to use when create AI. If you need more examples for each logic please use chatgpt.
AI Hardware - The machines Behind the Models3:15
Explore how artificial intelligence models run on hardware from cloud training to mobile inference, compare CPUs and GPUs, and learn about ASICs, SoCs, and neuromorphic chips.
AI Frameworks0:57
In this session, you will get to know about AI Frameworks. Just like how we use Framework as a tool to build our software system, we also use AI Frameworks to build AI systems. You don't have to learn all the frameworks, because these framework changes quick. However you need to know how to read framework document that's available and from the document you need to know how to use it, that's also how you should answer in interview.
AI as a service (AIaas) - How tester come into picture for the service3:28
Quiz 1:
What is Pre-trained Models0:57
In earlier session we have talked about one of the main ways to get AI components, do you remember? it was AIaaS. On this session we are going to talk about the another main way -- which is Pre-trained Models. Please check the course document to understand what is Pre-trained models, and differences with AIaas.
Transfer Learning and pre-trained models0:57
Please carefully read the document for transfer learning ~ it's a self study session.
Quiz 2

Machine Learning and main categories of ML0:57
Please read the document very carefully, this is a very easy session. You can just understand the whold concept by reading it.
ML Workflow4:31
ML Approach - how tester insight on these0:57
This self-study guide is designed to help learners independently understand how to select the right machine learning approach and recognize common modeling issues like overfitting and underfitting. Through real-world explanations and tester-focused insights, you’ll learn how to evaluate ML problems, choose between supervised, unsupervised, and reinforcement learning, and understand what factors influence algorithm selection. You'll also explore how model complexity can affect performance — and how to detect when things go wrong.
This guide requires no prior instruction and is written in an accessible, conversational style to support deep understanding even for self-paced learners.
Quiz 4

Data Prep in the ML Workflow and Real Time Practice5:18
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Quiz 5
Training, Validation, and Test Datasets - Self Study Session0:57
Master AI tester skills by understanding training, validation, and test datasets in a self-paced, accessible course. Read the official ISTQB AI testing syllabus to connect concepts and deepen understanding.
Practice Assignment0:02
Once you finish session course, please download the assignment and follow the instuctions, also download data set file use it as demo data for your assignment
Data quality issues - please download the resources0:57
Please download self study script
Understanding Data Labelling for Supervised Learning - Self Study Session0:57
Please download self study script

Specification and Test Levels of AI Based System5:46
Learn how to specify AI based systems with flexible, data-driven requirements, and apply a layered testing approach from input data testing, ML model testing, to component, integration, and acceptance testing.
Test Data Challenges & Automation Bias & AI Documentation3:29
Quiz 7
Concept Drift and ML Test Approach4:06
Learn to detect concept drift and implement an ml test approach combining risk analysis, data quality checks, and a/b testing to ensure explainable, robust models.

Requirements

Basic knowledge of Software Testing
Manual Testing experience is recommended
No prior AI knowledge is required

Description

Are you ready to step into one of the fastest-growing roles in the tech industry?

Artificial Intelligence is changing everything – including how we test software. This course is your complete roadmap to becoming an AI/ML Tester, even if you have no prior experience with AI or machine learning.

Based on the official ISTQB Certified Tester AI Testing (CT-AI) syllabus, this course gives you the practical knowledge and skills to understand AI systems and confidently test them. Whether you're a manual tester, automation engineer, QA lead, or aspiring tech professional, this course will help you stay ahead of the curve and land opportunities in this exciting and future-proof field.
- What You’ll Learn

The fundamentals of AI and machine learning, including key algorithms and data concepts
The challenges of testing AI-based systems and how they differ from traditional software
Hands-on techniques for adversarial testing, metamorphic testing, pairwise testing, back-to-back testing, and more
How to use AI tools to support software testing – including defect prediction, test case generation, and regression optimization
How to test machine learning models, evaluate data quality, and ensure fairness, transparency, and safety
Real-world AI testing practices and how to align them with industry standards like ISTQB CT-AI

- Who This Course Is For

Manual and automation testers looking to upskill into AI/ML testing
QA engineers and software developers curious about AI’s role in testing
Anyone preparing for the ISTQB AI Testing certification
Tech professionals interested in cutting-edge testing roles
Beginners in AI who want to break into this career path with clear guidance

Who this course is for:

Current Software Testers or QA Engineers who want to transition into AI Testing roles
Manual Testers who are ready to upgrade their skills and explore the AI market
Testers preparing for the ISTQB AI Testing Certification and need a structured, beginner-friendly guide
Junior QA professionals who want to understand how AI is changing the testing world
Anyone in software testing who wants to future-proof their career with AI-focused skills

Everything You Need to Become an AI Tester

What you'll learn

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Course content

Introduction10 lectures • 20min

Quality Characteristics for AI-Based Systems1 lecture • 5min

Machine Learning(ML)3 lectures • 6min

ML Data5 lectures • 8min

ML Functional Performance Metrics3 lectures • 10min

ML - Neural Networks and Testing2 lectures • 3min

Testing AI - Bases Systems Overview3 lectures • 13min

Testing AI-Specific Quality Characteristics1 lecture • 8min

Methods and Techniques for the Testing of AI-Based Systems2 lectures • 8min

Testing Environments1 lecture • 1min

Requirements

Description

Who this course is for: