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.
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 |