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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 units

solid line — the way is open · dashed — closed for nowView: map · steps

2 · closed

The Model You Picked Costs You Twice

~0.7 h

opens after “Same Prompt, Different Test Suite”

3 · closed

The Screenshot Your Model Cannot Read

~0.7 h

opens after “The Model You Picked Costs You Twice”

4 · closed

"Make Me Some Test Cases"

~1.1 h

opens after “The Screenshot Your Model Cannot Read”

5 · closed

Three Techniques, and Where Each Breaks

~1.1 h

opens after “"Make Me Some Test Cases"”

6 · closed

Finding the Holes in the Requirement

~1 h

opens after “Three Techniques, and Where Each Breaks”

7 · closed

From Acceptance Criteria to Test Cases

~1 h

opens after “Finding the Holes in the Requirement”

8 · closed

Gherkin at Scale

~0.9 h

opens after “From Acceptance Criteria to Test Cases”

9 · closed

The Regression Suite That Heals Itself

~0.9 h

opens after “Gherkin at Scale”

10 · closed

Reading a Failed Nightly Run

~0.8 h

opens after “The Regression Suite That Heals Itself”

11 · closed

Numbers the Partner Will Read

~0.7 h

opens after “Reading a Failed Nightly Run”

12 · closed

Choose the Technique Before You Write

~0.8 h

opens after “Numbers the Partner Will Read”

13 · closed

Proving the Output Is Good Enough

~0.9 h

opens after “Choose the Technique Before You Write”

14 · closed

It Sounded Right and It Was Wrong

~0.9 h

opens after “Proving the Output Is Good Enough”

15 · closed

Turning the Temperature Down

~0.7 h

opens after “It Sounded Right and It Was Wrong”

16 · closed

Client Data Does Not Leave the Firm

~1 h

opens after “Turning the Temperature Down”

17 · closed

Who Signs Off That This Was Legal

~0.9 h

opens after “Client Data Does Not Leave the Firm”

18 · closed

The Model Has Never Seen Your Test Cases

~1.1 h

opens after “Who Signs Off That This Was Legal”

19 · closed

The Agent That Filed Forty Bad Defects

~0.8 h

opens after “The Model Has Never Seen Your Test Cases”

20 · closed

When Prompting Is Not Enough

~0.9 h

opens after “The Agent That Filed Forty Bad Defects”

21 · closed

Shadow AI in an Audit Firm

~0.9 h

opens after “When Prompting Is Not Enough”

final · in the browser, without the assistant

Exam

closed · enrol on the course

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

1Same Prompt, Different Test Suite

Explain why an LLM returns different output for identical input

~0.8 hcan start
2The Model You Picked Costs You Twice

Distinguish the foundation, instruction-tuned and reasoning stages of LLM training

~0.7 hclosed
3The Screenshot Your Model Cannot Read

Write and execute a prompt combining a wireframe and a user story for a test task

~0.7 hclosed
4"Make Me Some Test Cases"

Give examples of the six components of a structured prompt for a test task

~1.1 hclosed
5Three Techniques, and Where Each Breaks

Differentiate prompt chaining, few-shot prompting and meta prompting

~1.1 hclosed
6Finding the Holes in the Requirement

Apply generative AI to identify defects in the test basis

~1 hclosed
7From Acceptance Criteria to Test Cases

Apply generative AI to generate test cases from acceptance criteria

~1 hclosed
8Gherkin at Scale

Use few-shot prompting to produce output in a fixed house format

~0.9 hclosed

Show the remaining 13 units