Generative AI for Software Testing: A Practitioner's Course
A hands-on course on using large language models across the test process: prompting for test analysis and design, evaluating what the model gives back, containing its risks, and rolling it out in an organisation that handles client data. Built around a professional-services engagement, where confidentiality and documented review are not optional. Assumes working knowledge of test design, test levels and defect management.
Material and exam: English · your assistant leads the lesson
How it works
Your assistant takes the course material from our server and leads the lesson in your language.
The exam is taken on the site, without an assistant. Exam questions are not translated: this is decided for every course.
Path through the course
· 21 unitstop to bottom · a unit opens when its conditions are metView: map · steps
Stage 1
~0.8 h
1 · can start
Same Prompt, Different Test Suite
~0.8 h
Stage 2
~0.7 h
2 · closed · opens after “Same Prompt, Different Test Suite”
The Model You Picked Costs You Twice
~0.7 h
Stage 3
~0.7 h
3 · closed · opens after “The Model You Picked Costs You Twice”
The Screenshot Your Model Cannot Read
~0.7 h
Stage 4
~1.1 h
4 · closed · opens after “The Screenshot Your Model Cannot Read”
"Make Me Some Test Cases"
~1.1 h
Stage 5
~1.1 h
5 · closed · opens after “"Make Me Some Test Cases"”
Three Techniques, and Where Each Breaks
~1.1 h
Stage 6
~1 h
6 · closed · opens after “Three Techniques, and Where Each Breaks”
Finding the Holes in the Requirement
~1 h
Stage 7
~1 h
7 · closed · opens after “Finding the Holes in the Requirement”
From Acceptance Criteria to Test Cases
~1 h
Stage 8
~0.9 h
8 · closed · opens after “From Acceptance Criteria to Test Cases”
Gherkin at Scale
~0.9 h
Stage 9
~0.9 h
9 · closed · opens after “Gherkin at Scale”
The Regression Suite That Heals Itself
~0.9 h
Stage 10
~0.8 h
10 · closed · opens after “The Regression Suite That Heals Itself”
Reading a Failed Nightly Run
~0.8 h
Stage 11
~0.7 h
11 · closed · opens after “Reading a Failed Nightly Run”
Numbers the Partner Will Read
~0.7 h
Stage 12
~0.8 h
12 · closed · opens after “Numbers the Partner Will Read”
Choose the Technique Before You Write
~0.8 h
Stage 13
~0.9 h
13 · closed · opens after “Choose the Technique Before You Write”
Proving the Output Is Good Enough
~0.9 h
Stage 14
~0.9 h
14 · closed · opens after “Proving the Output Is Good Enough”
It Sounded Right and It Was Wrong
~0.9 h
Stage 15
~0.7 h
15 · closed · opens after “It Sounded Right and It Was Wrong”
Turning the Temperature Down
~0.7 h
Stage 16
~1 h
16 · closed · opens after “Turning the Temperature Down”
Client Data Does Not Leave the Firm
~1 h
Stage 17
~0.9 h
17 · closed · opens after “Client Data Does Not Leave the Firm”
Who Signs Off That This Was Legal
~0.9 h
Stage 18
~1.1 h
18 · closed · opens after “Who Signs Off That This Was Legal”
The Model Has Never Seen Your Test Cases
~1.1 h
Stage 19
~0.8 h
19 · closed · opens after “The Model Has Never Seen Your Test Cases”
The Agent That Filed Forty Bad Defects
~0.8 h
Stage 20
~0.9 h
20 · closed · opens after “The Agent That Filed Forty Bad Defects”
When Prompting Is Not Enough
~0.9 h
Stage 21
~0.9 h
21 · closed · opens after “When Prompting Is Not Enough”
Shadow AI in an Audit Firm
~0.9 h
Exam
closed · enrol on the course
final · in the browser, without the assistant
Exam
The path in words
- Stage 1 · Same Prompt, Different Test Suite — can start; ~0.8 h
- Stage 2 · The Model You Picked Costs You Twice — closed; opens after “Same Prompt, Different Test Suite”; ~0.7 h
- Stage 3 · The Screenshot Your Model Cannot Read — closed; opens after “The Model You Picked Costs You Twice”; ~0.7 h
- Stage 4 · "Make Me Some Test Cases" — closed; opens after “The Screenshot Your Model Cannot Read”; ~1.1 h
- Stage 5 · Three Techniques, and Where Each Breaks — closed; opens after “"Make Me Some Test Cases"”; ~1.1 h
- Stage 6 · Finding the Holes in the Requirement — closed; opens after “Three Techniques, and Where Each Breaks”; ~1 h
- Stage 7 · From Acceptance Criteria to Test Cases — closed; opens after “Finding the Holes in the Requirement”; ~1 h
- Stage 8 · Gherkin at Scale — closed; opens after “From Acceptance Criteria to Test Cases”; ~0.9 h
- Stage 9 · The Regression Suite That Heals Itself — closed; opens after “Gherkin at Scale”; ~0.9 h
- Stage 10 · Reading a Failed Nightly Run — closed; opens after “The Regression Suite That Heals Itself”; ~0.8 h
- Stage 11 · Numbers the Partner Will Read — closed; opens after “Reading a Failed Nightly Run”; ~0.7 h
- Stage 12 · Choose the Technique Before You Write — closed; opens after “Numbers the Partner Will Read”; ~0.8 h
- Stage 13 · Proving the Output Is Good Enough — closed; opens after “Choose the Technique Before You Write”; ~0.9 h
- Stage 14 · It Sounded Right and It Was Wrong — closed; opens after “Proving the Output Is Good Enough”; ~0.9 h
- Stage 15 · Turning the Temperature Down — closed; opens after “It Sounded Right and It Was Wrong”; ~0.7 h
- Stage 16 · Client Data Does Not Leave the Firm — closed; opens after “Turning the Temperature Down”; ~1 h
- Stage 17 · Who Signs Off That This Was Legal — closed; opens after “Client Data Does Not Leave the Firm”; ~0.9 h
- Stage 18 · The Model Has Never Seen Your Test Cases — closed; opens after “Who Signs Off That This Was Legal”; ~1.1 h
- Stage 19 · The Agent That Filed Forty Bad Defects — closed; opens after “The Model Has Never Seen Your Test Cases”; ~0.8 h
- Stage 20 · When Prompting Is Not Enough — closed; opens after “The Agent That Filed Forty Bad Defects”; ~0.9 h
- Stage 21 · Shadow AI in an Audit Firm — closed; opens after “When Prompting Is Not Enough”; ~0.9 h
Programme · 21 units
| 1 | Same Prompt, Different Test Suite Explain why an LLM returns different output for identical input | ~0.8 h | can start |
| 2 | The Model You Picked Costs You Twice Distinguish the foundation, instruction-tuned and reasoning stages of LLM training | ~0.7 h | closed |
| 3 | The Screenshot Your Model Cannot Read Write and execute a prompt combining a wireframe and a user story for a test task | ~0.7 h | closed |
| 4 | "Make Me Some Test Cases" Give examples of the six components of a structured prompt for a test task | ~1.1 h | closed |
| 5 | Three Techniques, and Where Each Breaks Differentiate prompt chaining, few-shot prompting and meta prompting | ~1.1 h | closed |
| 6 | Finding the Holes in the Requirement Apply generative AI to identify defects in the test basis | ~1 h | closed |
| 7 | From Acceptance Criteria to Test Cases Apply generative AI to generate test cases from acceptance criteria | ~1 h | closed |
| 8 | Gherkin at Scale Use few-shot prompting to produce output in a fixed house format | ~0.9 h | closed |