Course Overview
This course provides comprehensive preparation for the ISTQB Certified Tester – Generative AI (CT-GenAI) certification. It covers foundational concepts of Generative AI and Large Language Models (LLMs), practical prompt engineering techniques, and the unique risks and challenges in testing GenAI systems. The course also explores modern test infrastructure including RAG, AI agents, fine-tuning, and LLMOps, as well as the evolving roles and workflows in QA teams adopting GenAI.
Designed for testers, QA engineers, and AI enthusiasts, the course aligns closely with the official ISTQB syllabus and includes over 200 practice quizzes to build exam confidence and practical understanding.
Key Takeaways
- Understand core Generative AI and LLM concepts as defined in the ISTQB CT-GenAI syllabus.
- Apply prompt engineering techniques to design effective, testable AI-generated outputs.
- Identify and mitigate risks, biases, and failure modes unique to GenAI systems.
- Explore RAG architecture, AI agents, fine-tuning, and LLMOps in test automation infrastructure.
- Learn how GenAI is reshaping QA roles, workflows, and adoption strategies.
- Prepare confidently for the ISTQB Certified Tester – GenAI exam with concept-to-question mapping.
Prerequisites
None. No prior AI experience is needed.
Target Learners
- Software Testers
- QA Engineers
- AI Enthusiasts
What is ISTQB Gen AI Testing Certificate & Get details 7:22
Important Note Before You Begin 0:41
Understand the AI Spectrum and its evolvement over Years as Machine Learning 5:45
What is Deep Learning & How different it is from Machine Learning underhood 7:09
What is Generative AI & LLM? - Understand with Scenarios 8:02
What are Tokens & Embeddings in the context of LLM and their importance 9:15
Why there is Non Determinism in LLM Outputs. Internal working mechanism 4:40
Understand the Importance of Context Window in LLM Session 3:44
3 Type of LLM's - Foundational ,Instruction Tuned & Reasoning LLM's - Know Diff 7:07
Learn Key LLM Capabilities for Testing Tasks with examples 5:04
AI Chatbots vs LLM Powered Testing Applications - Understand the Difference 5:29
Download the Slides/Notes discussed from this Chapter 0:01
Chapter 1 - Recap 0:21
Exam Focus / Key Takeaways 0:26
Quizzes - Multiple Choice Exam Pattern questions
Why Prompt Engineering Matters? & Key components of Prompt 5:27
The 6 Parts of Prompt Structure with the importance of each Part with examples 6:20
What is Prompt Chaining? When this technique should be used with example 5:57
What is Meta Prompting? When this technique should be used with example 7:51
Test Analysis with Gen AI - Understand the context and drive the results from AI 6:28
How to perform Automated Regression Testing with Gen AI with examples 8:11
Techniques for refining Prompts - How to get better results from LLM 7:34
Download the Slides/Notes discussed from this Chapter 0:01
Chapter 2 - Recap 0:25
Exam Focus / Key Takeaways 0:31
Quizzes - Multiple Choice Exam Pattern questions
What is Hallucination & Reasoning errors for LLM outputs 6:37
What is Bias in LLM outputs? Understand with examples 5:12
How to Detect Hallucination & Reasoning errors from LLM output - Know techniques 5:47
Mitigating Hallucinations, Reasoning errors & Biases of LLM outputs 5:06
How Temperature & Random seeds factors play a key role in LLM Non Determinism 4:36
Understand Data privacy & Security risks involved with Gen AI usage in Project 7:23
Mitigating Data privacy & Security risks with Gen AI Adoption - Techniques 6:17
AI Regulations, Standards & Best Practice Frameworks in Gen AI Adoption 4:33
Download the Slides/Notes discussed from this Chapter 0:01
Chapter 3 Recap 0:31
Practice Exam 1
Understand LLM Architecture components - Front end, Backend 8:10
Backend Data sources & Post processing the data -Relation db & Vector database 4:45
What is RAG Architecture? Understand internal working mechanism 11:00
How RAG Pipeline works - Setup phase & Query phase 8:20
LLM Powered Agents : What makes them different? & Autonomy levels of Agent 11:54
What is Fine Tuning LLM? In what Scenarios we need Fine tuning route 8:51
LLM OPS - Operationalizing Gen AI & Approaches followed for Gen AI Testing 10:18
Download the Slides/Notes discussed from this Chapter 0:01
Chapter 4 Recap 0:27
Quizzes: Quiz 3: Multiple Choice Exam
Understand the risk invovled in Shadow AI with examples 4:33
Key Aspects of Gen AI Test Strategy - How you measure outcome of Gen AI Adoption 7:06
Selecting the right LLM for Testing tasks - Factors to consider for evaluation 6:50
Three Phases of Gen AI Adoption - Discovery -Initiation - Utilization 4:47
Essential Skills & Knowledge for Testers working with Gen AI 7:44
How Tester roles evolves with Gen AI for both Mid level & Manager level testers 6:12
Download the Slides/Notes discussed from this Chapter 0:01
Access Files No pi required.
Free Course files 1 file package
- Full Pack
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