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AI-QA-01LIVE ONLINE
Turn AI into a practical quality engineering skill
Applied AI for QA Engineers
Move beyond casual prompting and build AI-assisted QA workflows you can explain, evaluate and improve.
Understand how modern AI works, compare leading models, run a local model and apply reliable prompting, retrieval and agent workflows to quality assurance.
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LEVELBeginner to advanced
FORMATLive online on Zoom
STARTING POINTBasic software testing knowledge is helpful. No previous AI or coding experience is required.
SUPPORTWhatsApp group, Google Drive and continued guidance
01 / THE OUTCOME
What you will be able to do.
Manual testers, automation engineers, QA leads and developers who want to use generative AI responsibly in real testing work.
- 01
Explain the relationship between AI, machine learning, deep learning and large language models
- 02
Compare GPT, Claude, Gemini and open-source models for different QA tasks
- 03
Run a local model with Ollama and recognise limits, hallucinations and context constraints
- 04
Create reusable prompts for test cases, test data, defect reports and log analysis
- 05
Choose between prompting, retrieval-augmented generation, fine-tuning and agents
- 06
Build and present an AI agent that turns a work item into reviewed test ideas or scripts
02 / FULL CURRICULUM
A clear path from foundation to practical result.
Each module builds on the previous one. Open a module to see the main topics.
M01AI foundations and the model landscapeUnderstand the essential concepts, compare model choices and run a model locally.
- AI, machine learning and deep learning
- Supervised and unsupervised learning
- GPT, Claude, Gemini and Llama
- Context windows, pricing, openness and model strengths
- Ollama setup with Llama or Mistral
- QA uses such as test design, test data and log analysis
M02How large language models workBuild a practical mental model of tokens, embeddings, transformers and model controls.
- Tokenisation and embeddings
- Transformers and self-attention
- Query, key and value concepts
- Pre-training and fine-tuning
- Temperature, top-p and token limits
- Consistency, creativity and hallucination risk
M03Prompt engineering for QA workUse a repeatable framework to produce more useful, reviewable QA outputs.
- The ICED-TO prompt framework
- Instruction, context, examples, data, tone and output format
- Role prompting and few-shot examples
- Test case and test data generation
- Defect report and risk analysis prompts
- Building a reusable QA prompt library
M04Retrieval, agents and job-ready applicationMove from individual prompts to grounded workflows, tools and a portfolio project.
- Retrieval-augmented generation and fine-tuning
- AI agents, tools, memory and workflows
- LangChain and LlamaIndex concepts
- AI support for Selenium and Playwright automation
- CV, LinkedIn and interview preparation with AI
- Responsible use, verification and data privacy
03 / PRACTICAL PROJECT
QA ticket-to-test AI agent
Build a focused AI workflow that reads a realistic Jira-style work item and produces reviewed test ideas or Playwright test scaffolding. You will explain the model choice, prompt design, verification steps and limitations.
WHAT YOU WILL PRODUCE
- 01Model comparison and evaluation notes
- 02Reusable QA prompt library
- 03Working ticket-to-test agent workflow
- 04Project walkthrough with risks and verification decisions
04 / HOW YOU LEARN
Structure that keeps you moving.
Guided practice
Try the work in manageable steps while the method is still fresh.
Focused feedback
Understand what is working and what will improve your next attempt.
Independent result
Bring the skills together in work you can review, keep and explain.
05 / QUESTIONS
Know what to expect before you enrol.
For timetable, weekly commitment or payment questions, message us on WhatsApp.
Do I need previous AI or coding experience?
No. The course begins with the core concepts and model landscape. Basic testing knowledge helps you connect each AI technique to realistic QA work.
Is this only for automation engineers?
No. Manual testers can use the course for test design, data, defect communication and analysis. Automation engineers also explore AI-assisted script generation, debugging and agent workflows.
How are live classes and course updates delivered?
Classes are taught live online on Zoom with practical examples, guided work and time for questions. After joining, you are added to a course WhatsApp group where meeting links, reminders and course updates are shared.
Where can I find recordings and study material?
You receive a shared Google Drive folder containing course recordings, study material and practice resources. The folder remains available after the course, so you can revisit lessons and continue practising.
Can I continue to ask questions after the course?
Yes. The course WhatsApp group remains available after completion. You can continue to clarify course-related doubts, ask for guidance and use the shared material while developing your skills.
READY WHEN YOU ARE
Make this the skill you stop postponing.
Review the curriculum, confirm any questions and enrol securely through Stripe.