AI Software Testing: Zero to Job-Ready QA, No Coding

Name: AI Software Testing: Zero to Job-Ready QA, No Coding
Rating: 4.3 (29 reviews)

Learn software testing with AI from scratch — automate with Playwright, find real bugs, get job-ready. No coding needed

Created byAsim Noaman Lodhi

Last updated 8/2026

English

English [Auto],

What you'll learn

AI-Powered QA Testing: Beginner to Job-Ready (No Code)
Understand core software testing concepts from scratch — test plans, test cases, test data, bugs, and severity.
Use AI and LLMs as a QA tester, with deep hands-on work in Claude Code
Write professional test plans and test cases from plain-English requirements using the 3 C's of prompting.
Build and run automated browser tests with Playwright — without needing a coding background.
Direct AI agents to write tests, drive the browser, and generate full test suites for you.
Diagnose and fix failing tests using the run → read → ask → fix loop with AI assistance.
Find real bugs and write clear, reproducible bug reports that developers respect.
Build a job-ready QA portfolio project on GitHub with a recruiter-friendly README.

Course content

10 sections • 51 lectures • 5h 34m total length

Introduction5:10
Master software quality assurance from zero to job-ready without coding, using AI automation to boost productivity, cover foundations, setup and testing planning, and portfolio building to land roles.
Using an AI Agent to Test Software: What We'll Build2:00
Plan end-to-end testing with an ai agent, turning requirements into test plans and cases. Build a real browser test, generate bug reports, and showcase a portfolio piece for job-ready qa.
Why Software Breaks (and Why QA Testers Exist)4:10
Explore what software testing is, why QA testers exist, how manual vs automated testing catches bugs before release, and how AI-augmented, human-in-the-loop testing works with login pages.
Manual vs Automated Testing: Key Differences Explained5:00
Explore manual testing as real user exploration and compare it with AI-driven automated testing. Build a concise plan covering scope, environments, resources, tools, test cases, data, and severity.
What a Real Test Case Looks Like (With Example)6:13
Think Like a Tester: Your First Hands-On Exercise1:53
Think like a tester during a hands-on login form exercise; create three test cases for empty fields, a wrong password, and a 200-character name with spaces, with expected results.
How to define Software Test Strategy7:53
Define a robust software test strategy using smoke testing for quick build stability and sanity testing for targeted verification, illustrated by automating GUI tests with a test control window.

Prompt Engineering for QA - I2:46
Examples of Prompt Engineeering for QA3:11
Hands On Practice Excersise for Prompt Engineering4:56
Hands On Practice Excersise for Prompt Engineering II8:39
Hands on Practice Excersise Prompt Engineering III8:25
Build a AI Powered Testing Framework7:53
Learn to tame ai in qa by applying the Craft framework—context, role, action, format, and target audience—using defensive prompts, guardrails, and a three-step refinement loop for reliable, autonomous testing.
Prompt Engineering Framework for QA Testers7:30

Understanding LLMs in Software Testing (Plain English)5:08
Understand large language models (LLMs) and AI agents in software testing, including prompts, tokens, and context windows, and learn a divide-and-conquer approach for crafting tests.
Why You Should Never Blindly Trust AI (Hallucinations)6:21
Discover why you should never blindly trust ai, as hallucinations can mislead tests; maintain human in the loop and harness strong prompts and ai agents.
Why You Should Never Blindly Trust AI (Hallucinations)6:56
Set up four free tools, plan tests with AI, and run your AI augmented test using Playwright and VS Code on a demo e-commerce app to validate login and checkout.
When Setup Breaks: Fixing Common Errors (Don't Panic)3:28
Lets Talk with Alex to Understand LLM, Testing With AI Tools

Introduction to Claude AI + Microsoft Playwright5:04

Playwright Latest News Tips and Tricks Blog:

https://playwright.aims-ai.com
30-40-30 Rule3:18
Apply the 30-40-30 rule to automate tests with playwright code gen, blending automated scripts and 30% manual editing, while mitigating token use with MCP server setup and cloud code.
Setting Up Your Project Folder in VS Code (Step by Step)3:20
How to setup Project in VS Code12:20
Set up a new Microsoft Playwright project in VS Code using cloud code, connect your paid account, choose a language, enable GitHub actions, and install the mcp server.
Setting Up Your Project Folder in VS Code (Step by Step)17:40
Set up and configure your VS Code project folder with an mcp server, access cloud code via terminal, and create a QA automation agent using Playwright and mcp tools.
Setting Up Your Project Folder in VS Code (Step by Step)7:19
How to Create Test Scripts with AI Agents (Step by Step)8:42
How to Run Scripts5:21
Playwright Latest News Tips and Tricks Blog:

https://playwright.aims-ai.com
Section 4 — Hands-On Exercise

Multi-Agent AI Test Automation with Playwright and Claud4:09
Orchestrator Agent Explained: Coordinating Playwright Test Agents3:49
Explore how an orchestrator agent acts as a virtual team lead to delegate tasks to specialized playwright qa automation, business analyst, and designer agents, enabling multi-agent coordinated testing.
Worker Agents: Generating and Validating Playwright Tests5:44
Learn how worker agents generate and validate playwright tests from clear requirements, acceptance criteria, and edge cases, guided by an orchestrator and specialized QA agents.
Running Your Multi-Agent Playwright Workflow End to End3:55
Coordinate a multi-agent Playwright workflow end to end, with specialist agents handling requirements, code, tests, and deployment, all managed by an orchestrator for automated task delegation and traceability.
Running Playwright AI Agents in VS Code: Setup and Execution14:46
Creating Custom Subagents in Claude Code for Playwright Tests6:37
Create custom subagents in Claude code to orchestrate playwright tests and delegate tasks via an orchestrator in a multi-agent system with cloud code and cloud.md context.
Building Orchestrator and Interface Subagents in Claude Code7:59
Build a multi-agent system with an orchestrator and subagents—business analyst, code reviewer, and front-end developer—to design, implement, and QA a landing page using Claude code.

Basics of Agile vs Scrum & Sprint Model5:31
Basics of JIRA Terminologies9:46
Types of Projects in JIRA10:57
Understanding JIRA Interface11:07
Explore the Jira interface, including your work, dashboards, filters, and issues, with emphasis on recent and starred items. Navigate with the app switcher, create issues, and manage permissions and notifications.
How to create Issues in JIRA8:25
Rovo AI in Jira — Step-by-Step Setup Guide for Beginners8:09
Discover how to set up and use rovo, the Jira AI tool, to filter bugs, create dashboards and charts, generate JQL queries, and track open issues for better team compliance.
Practice Test For JIRA

Requirements

No prior software testing experience needed — this course starts from absolute zero.
No coding or programming background required; the AI writes the code while you learn to direct and verify it.
A computer (Windows, Mac, or Linux) with a stable internet connection.
Willingness to install free tools (VS Code, Node.js, Playwright) — all guided step by step.
A free AI assistant account (Claude or GitHub Copilot) — both free options are shown in the course.

Description

Want to break into tech — without a computer science degree or years of coding?

Software testing (QA) is one of the most realistic ways to start a tech career, and AI has just made it far more accessible. Companies everywhere now want testers who can use AI tools to test smarter and faster. This course takes you from complete beginner to job-ready — no coding background required.

You won't just watch theory. You'll work on one real, hands-on project from start to finish: you'll test a real demo web application, and by the end you'll have a portfolio project you can show in interviews.

Here's what you'll do, step by step:

Understand what software testing really is — test plans, test cases, bugs, and severity — starting from absolute zero.
Learn how AI and Large Language Models (LLMs) actually work, in plain English, and how to use them safely as a tester.
Set up your free toolkit (VS Code, Playwright, and an AI assistant like Claude or GitHub Copilot) with step-by-step guidance.
Use AI and smart prompt engineering to turn plain-English requirements into professional test plans, test cases, and test data.
Build and run automated browser tests with Playwright — letting AI write the code while you stay the decision-maker.
Direct AI agents to drive the browser, generate whole test suites, and even help fix failing tests.
Find real bugs and write professional bug reports that developers respect — and log them in Jira, just like real teams do.
Package your work into a polished GitHub portfolio with a README that recruiters can skim in 60 seconds.
Walk away with resume bullet points, answers to common AI-QA interview questions, and a concrete 30-day action plan to land the role.

Who's teaching you: this course is built by a working QA professional, structured so a true beginner can follow every click without getting lost.

Why now: manual-only testing roles are shrinking, while demand for testers who can work with AI is growing fast. The most in-demand profile in 2026 combines solid testing fundamentals with AI-tool literacy — exactly what you'll build here.

By the end of this course you will be able to: plan tests with AI, automate them with Playwright, find and report real bugs, and present a complete project that proves you can do the job.

No prior testing or programming experience is required — just a computer and curiosity. Enroll now and start building your path into tech today.

Who this course is for:

Complete beginners who want to start a career in tech without a degree or coding background.
Career switchers from non-tech roles (support, operations, admin, customer service) moving into QA.
Aspiring QA / software testers who want modern, AI-powered skills that employers are hiring for in 2026.
Manual testers who want to stay relevant by learning AI-assisted automation and Playwright.
Bootcamp grads and students looking for a realistic first tech role with a portfolio to prove it.

AI Software Testing: Zero to Job-Ready QA, No Coding

What you'll learn

Explore related topics

Course content

Introduction to AI Software Testing7 lectures • 32min

Prompt Engineering for Testers7 lectures • 43min

Understanding LLMs in Software Testing (Plain English)5 lectures • 22min

Planning Test Cases with AI: A Step-by-Step Guide3 lectures • 15min

AI Augmented Software Testing with Claude AI + Microsoft Playwright8 lectures • 1hr 3min

Multi-Agent AI Test Automation with Playwright and Claude7 lectures • 47min

Best AI Tools for QA Engineers2 lectures • 7min

Github Copilot AI Agents5 lectures • 35min

JIRA Project Management Tool6 lectures • 54min

Understand Test Strategy2 lectures • 16min

Requirements

Description

Who this course is for: