10
Live Sessions
120 mins
Session Length
Applied Learning
Level
Professionals
Suitable For
Live Online
Delivery
UK Time
Time Zone
LEARNING OBJECTIVE
By the end of this course, you will be able to
Build test cases from a requirements document or user story using ChatGPT or Claude, covering boundary conditions and negative scenarios a manual pass alone tends to miss.
Automate the first draft of a defect report from a rough description, cutting the time between finding a bug and logging it clearly.
Present a release sign-off summary generated from your test execution results that a stakeholder can act on without follow-up questions.
Justify which AI-generated test suggestions to keep and which to discard, because not every suggestion is a good one.
Lead your team's first conversation on where AI actually helps in manual QA, backed by a working prompt library you built and tested.
TARGET LEARNER
Who this course is for
For manual testers ready to stop feeling left behind by AI and start using it every day.
Manual QA testers who want AI tools to help them work faster and smarter in their current role.
QA professionals under pressure to adopt AI but unsure where to start or what's actually useful.
Test analysts who want higher-quality test cases, better defect reports, and clearer QA summaries.
Senior manual testers who want to stay relevant as AI changes how testing gets done.
If you see yourself in one of these, this course is built for you.
Prerequisites
What you need
Manual testing experience is required before joining this course.
- At least six months of professional manual QA or software testing experience is expected.
- Familiarity with writing test cases, executing test cycles, and raising defect reports is needed.
- Basic computer literacy and experience using web-based tools is sufficient.
- No coding, automation, or AI experience is required — this course is designed for practising manual testers.
COURSE OVERVIEW
What this course is about
AI for Manual Testers is a practical, instructor-led programme for QA professionals who want to use AI tools to work better, not replace the testing skills they already have. The course covers AI-assisted test case design, test data generation, exploratory testing, and defect reporting in depth, combining live demonstration with real prompting practice throughout every session.
The programme runs across 10 two-hour live sessions, progressing through AI foundations for testers, test case design, and test data generation before finishing with AI-assisted exploratory testing, defect reporting, and a personal prompt library. Every topic is taught in the order it appears in a real manual testing cycle.
ChatGPT, Claude, and related AI tools are used throughout the course, with no coding required at any point. Prompting exercises are built around real testing scenarios from session one so learners are producing usable QA output throughout, not just in the final sessions.
What the course covers:
AI Foundations: prompting fundamentals and where AI fits into the manual testing lifecycle.
Test Case Design: generating detailed test cases from requirements, user stories, and acceptance criteria.
Test Data and Exploratory Testing: realistic test data generation and AI-assisted exploration techniques.
Reporting: clearer defect reports and stakeholder-ready test summaries.
Personal Workflow: a reusable AI prompt library built across the course.
CIRRICULUM
5 Modules. 10 live Sessions. Hundreds of small wins.
The curriculum starts with AI foundations for testers, then moves through test case design and test data generation before finishing with exploratory testing and defect reporting. Each module builds a piece of the AI prompt library you take back to work.
01
AI Foundations for Manual Testers
Understand what AI tools are genuinely useful for QA, how ChatGPT and Claude work, and the prompt engineering basics every tester needs to get high-quality output, including an honest assessment of what AI cannot do in a testing context.
02
AI for Test Case Design
Use ChatGPT and Claude to generate thorough positive, negative, and edge case test scenarios from user stories, acceptance criteria, and requirements documents, and apply a structured review process to evaluate the output before using it.
03
AI for Test Data Generation
Generate structured, realistic, and boundary-condition-aware test data using AI prompting techniques (covering valid data, invalid data, edge cases, and adversarial inputs) while understanding the data privacy boundaries that apply to AI tools.
04
AI-Assisted Exploratory Testing
Use AI to plan exploratory testing sessions, generate test charters, surface relevant heuristics, prioritise testing by risk, and document session findings, turning AI into a thinking partner for exploratory work.
05
AI for Defect Reporting and Test Summaries
Use AI to write clearer defect reports, generate root cause hypotheses, produce stakeholder-ready test execution summaries, and build a personal library of reusable AI prompts covering every testing activity learned across the course.
Course Types
We offer three structured learning paths based on your goals:
Crash Course (Fast-Track)
Quick, intensive courses designed to teach specific skills efficiently. Ideal for those upskilling fast or preparing for certifications.
DeepDive Program (Full Mastery)
Comprehensive, step-by-step learning for full mastery. For beginners and professionals seeking long-term, deep expertise.
MentorConnect (One-on-One)
Personalised mentorship with real-world guidance. Best for those who thrive with direct, expert-to-learner coaching.
Learning Approaches
We recognize that everyone learns differently, so we offer flexible learning formats to fit your needs:
One-on-One Training
Personalized, instructor-led coaching tailored to your learning speed.
Best for career-specific coaching or specialized training needs.
Small Batch Classes (2-5 learners)
Interactive, discussion-based learning in small groups.
Encourages collaboration, teamwork, and peer-to-peer engagement.
FAQ
1
Do I need any coding or automation experience for this course?
No coding or automation experience is required at any point. This course is designed exclusively for practising manual testers. Every AI tool is used through natural language prompting in a browser. No programming, no scripts, no technical setup beyond a laptop and an internet connection.
2
What AI tools will I use during the course?
The course primarily uses ChatGPT and Claude, both of which are accessible through a web browser. No paid subscriptions are required to get started, free tiers of both tools are sufficient for the majority of course exercises, and the tutor provides guidance on when a paid plan provides meaningful additional capability.
3
Will AI replace manual testers?
This is addressed directly in Module 1. The honest answer is that AI is changing the manual testing role, but it is not eliminating it. Testers who learn to use AI tools effectively will be significantly more productive and valuable than those who do not. This course is about becoming the tester who uses AI well, not the tester who worries about being replaced by it.
4
Will the test cases AI generates actually be usable?
AI-generated test cases require review and refinement. The course teaches you exactly how to do that. A dedicated quality checklist module covers the most common errors in AI test case output and how to correct them before using the results in your test suite. The goal is a productive human-AI collaboration, not unchecked AI output.
5
What is a prompt library and why will I need one?
A prompt library is a collection of tested, reusable AI prompts for your most common testing activities, generating test cases from a user story, creating boundary value data, writing defect reports, and producing test summaries. Module 5 is dedicated to building yours. A good prompt library is one of the most immediately useful outputs you will take back to your current role.
6
How quickly will I be able to use these skills in my current job?
Most learners use at least one technique from this course in their working week by Module 2. The course is designed for immediate practical application, every module includes exercises using realistic testing scenarios, and the prompt patterns taught work with the same types of documents and artefacts you work with in your current role.
7
Does the course cover data privacy when using AI tools?
Yes. Module 3 includes a dedicated section on data privacy considerations for AI tools in a testing context. You will learn what you should and should not include in AI prompts, how to anonymise real data for AI use, and what your organisation's AI usage policy likely requires. An increasingly important topic as AI tools become standard in the workplace.
8
Is this course relevant if I work in an Agile team?
Yes. The course content maps directly to the artefacts and activities in an Agile QA workflow. Generating test cases from user stories and acceptance criteria, producing sprint testing summaries, and planning exploratory testing sessions within a sprint are all covered with Agile-specific examples and prompt patterns.
9
Can I use these techniques with any type of application?
Yes. The prompting techniques in this course work across web applications, mobile apps, APIs, and desktop software. Module 2 and Module 3 both include exercises using different application types, and the personal prompt library you build in Module 5 is designed to adapt to any project context you work in.
10
What comes next after this course for a manual tester interested in AI?
Natural progressions from this course include the QA-to-AI Career Transition Program for those who want to move into AI-adjacent roles, or the AI for Automation Testers course for those who already have automation skills and want to integrate AI into a test framework. ITLearnner can advise on the best path based on your current skills and career goals.
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