CHATGPT for Software Testing | Generative AI

Name: CHATGPT for Software Testing | Generative AI
Rating: 4.4 (1147 reviews)

Learn how to use Chat GPT for day to day work in Software Testing. CHAT GPT for Programming and Testing

Created byDan Andrei Bucureanu

Last updated 10/2025

English

German [Auto],English [Auto],

What you'll learn

How to use ChatGPT for Quality Engineering
Improve Test automation with ChatGPT
Setup CI/CD pipelines with ChatGPT
Improve efficiency of working with CHATGPT
Perform validation for stories with Generative AI
Create an automated Playwright testing Framework with GPT 40 and CANVAS
Learn how to understand SQL and generate Test Data with Chat GPT
Generate and manipulate large Data Sets with AI Chat GPT
Create a full performance test framework with Jmeter in the cloud
Understand Basic Machine learning Methods
Build your own GPT and publish it to Marketplace
Connect to GTP with the help of the Rest API
Learn how to use ChatGPT to write BDD scenarios

Course content

13 sections • 106 lectures • 8h 31m total length

Introduction2:18
About your instructor2:00
Meet the instructor whose 20-year quality engineering career spans startups, banks, and industrial code, leading teams from two to eighty and shaping the field through ongoing learning.
Do not skip - AI for Testing the DOs and DONTs21:39
Understand what are the limitation, what you can and cannot do in all phases of a software testing project
Prompt Anatomy3:52
Master prompt anatomy for software testing with generative AI, outlining context, role, tone, and problem details, plus cascade prompting in automotive software contexts.
Chat GPT Model 01 and Chain of Though Prompts3:41
Understand CoT(Chain of thought) and model 01 internal reasoning
Link tot research paper: https://arxiv.org/pdf/2201.11903

What makes up AI3:47
Get a brief introduction on what are the main components of AI
Introduction to Natural Language Processing NLP4:56
How NLP actually makes the AI more human.
Types of Machine Learning4:08
Understand what is machine learning and how algorithms make the core of AI
Machine Learning - Supervised ML4:01
Understand the basics concepts around supervised Machine Learning
Machine Learning - Unsupervised ML5:03
Gain basic understanding of Unsupervised ML and Clustering
Machine Learning - Reinforced ML3:20
In this lecture you will get a basic idea of how Reinforced Learning is working together with ML Algorithms
Neural Networks and Deep Learning5:26
Explore how neural networks mimic brain connections with input, hidden, and output layers, using weights and transformations to learn patterns via supervised learning and deep learning when layers exceed three.
Importance of Training Data4:09
In this material you will understand how critical good quality training data actually is.
Transformer Architecture Model0:03
How to achieve repeatable and consistent GEN AI Outputs6:11
Warning - Hallucinations - Examples1:48
Warning - Privacy - Examples1:54

Understand Models and PLUS Subscription5:37
Explore openai's models GPT four, zero one preview, and A01 mini, pricing and uses, and how the GPT plus subscription offers priority access to Dall-E, file upload, and code interpreter.
GPT 4o with Canvas - A great piece of Work5:23
Get some insights into CHAT GPT with Canvas Editor
Features - Code interpreter -PLUS Subscription2:58
Build your custom GPT1:41
GPT Mentions | GPT Store2:32
platform.openai.com5:10
Great productivity hack with OPEN AI Mobile app6:30
Link to android app -> https://play.google.com/store/apps/details?id=com.openai.chatgpt&hl=en&gl=US
Link to apple app -> https://apps.apple.com/us/app/chatgpt/id6448311069

Self Healing Code - A proposal2:14
Discover AI assisted code coverage, or self-healing code, by training a model on your code and coverage reports to generate missing unit tests and reinforce learning through feedback.
AI Use Case 1- [Demo Generative AI] Self Healing Code - GItHub3:55
Explore a GitHub CI workflow where AI fixes code and writes unit tests to raise code coverage above thresholds, triggering repeated commits until checks pass, with human review for quality.
AI Use Case 2- Tests based on Analytics - Preconditions4:57
AI Use Case 2- Tests based on Analytics - How it Works4:56
Explore a next generation testing framework that uses analytics to drive continuous acceptance testing and production monitoring, via given–when–then scenarios fed by user behavior and model insights to prioritize usage.
AI Use Case 3 - Test Case Generation10:50
Train your AI with UI details, mocks, and existing test scripts to generate valid Selenium test cases, aligned with your page object model and company best practices.

Use ChatGPT to help understand any concept6:09
Rapid Start your documentation10:14
Learn to generate a high level ERP test strategy with ChatGPT using basic, intermediate, and advanced prompts, zero-one preview, canvas editing, and comprehensive risk-based cross-module testing for automation and performance.
Use CHATGPT to help in creating an robust test framework8:53
Use ChatGPT to validate and enhance User Stories4:57
Using ChatGPT for generating Test Cases from Acceptance Criteria9:55
Learn how to generate user acceptance tests and acceptance test templates with ChatGPT, crafting given-when-then scenarios from a user story, covering functional and nonfunctional requirements.
Understand how to use Chat History to keep context4:26

See the application under Test - Blazedemo.com1:58
Selecting best framework for the chosen website3:52
Use Chat GPT to select from multiple frameworks and compare so that you get the right one.
Installing VS Code2:40
Installing NODE2:47
Setting up the Prerequisites with GhatGPT2:55
Install Playwright and Demo Test5:16
Run npm install playwright, set up a working folder, install browsers with npx playwright install, and run tests with npx playwright test to capture a screenshot.
Deciding what is most important for Testing4:53
Completing the Test and generating first Draft Code with Mini o1 Model5:54
Understand how to extend the test and generate the first script - Spoiler it will not be usable from the beginning
Debug manually code6:43
Code Debug with ChatGPT 01 and Canvas7:58
Adding Screenshots for the tests3:27
Add logs and capture screenshots after each test step to simplify debugging and root-cause analysis within the playwright automation framework.
Best Practices and some future considerations9:00
How to use GPT 4o with Canvas to format code according to industry best practices such as decoupling, page object model and configuration files.

Open AI Codex - Understand what is Codex - 01 Agent3:41
Open AI Codex - Configure Codex for your environment7:11
Open AI Codex - Configure the Agents.md File5:50
Configure the agents md file for ai-driven test automation with playwright and a page object model, using repository workflows. Include config.json settings, installation steps, and pull request guidelines.
Open AI Codex - Create a powerful Agent.md file - fix the previous one7:00
Fix a poorly written agent.md for OpenAI Codex by defining agent instructions, config, tests, and data so tests run only when instructed.
Open AI Codex - Use Codex to generate invalid test data6:51
Open AI Codex - Generate Test that use invalid test data to simulate failure7:59

Generate Given When Then Scenarios2:07
Generate Cucumber Feature Files2:08
Generate cucumber feature files to automate test coverage using Gherkin-inspired scenarios, feature files, and Cucumber Java, while defining keywords and aligning with your system's syntax.
Generate Cucumber files with project context1:56
Generate Automated Tests with Chat GPT2:28
Learn to generate automated tests with ChatGPT by drafting Java-based WebDriver tests, mapping elements with a page object model, and validating scenarios from cucumber feature files.
Generate Automated Tests with project context2:00
Transform from Code to BDD - Cucumber2:49
Reverse engineer Selenium WebDriver Java tests into Cucumber feature files to produce human-readable scenarios for management and audits, using ChatGPT to bridge code and Cucumber.
Adapting code with CHATGPT2:23
Generate API call from Source Code3:31
Test the api by crafting a json payload for a calculator exposed on port 80 localhost, calling post methods for addition, subtraction, multiply, divide, and invalid operation, and validate results.
Using Chat GPT to help configure Postman3:15
Setting up CLI Execution for Postman2:23
Learn to run a Postman collection from the CLI on Windows using Newman after installing Node.js and npm, enabling CI/CD test runs after pull requests.
Switch from one format to another Postman -> Rest assured3:41
Generate Test Data with AI2:52
Generate SQL Queries5:33
Generate sql queries against a three-table database (customers, products, orders) using ChatGPT. Build selects, inner joins, inserts, and transaction-based scripts with realistic test data.
Import from Excel to SQL6:17
Generate large volumes of data4:48
Setup Containers with AI - Docker5:22
Using AI to add jobs in CI/CD pipeline4:23
Leverage generative AI to add a Postman test job to a GitHub Actions CI/CD pipeline, running on Ubuntu, installing NodeJS and Newman, and setting up Postman API key after deploy.
Using AI for setting up performance testing pipelines - GOOGLE LIGHTHOUSE4:17

Agentic AI | AI Agents - What are AI Agents5:22
Explore AI agents as orchestrators coordinating large language models, tools, and databases to automate tasks and enable scalable software development with prompt chaining and feedback loops.
Agentic AI - Demo On AI Agent that can Automatically Create Tests6:43
Agentic AI | AI Agents - What is Flowise AI3:44
Agentic AI | AI Agents - Installing Flowise AI Locally5:05
Agentic AI | AI Agents - Prompt Chaining9:42
Agentic AI | AI Agents - Interact with files6:58
Agentic AI | AI Agents - Generate Automated Tests from Webpage12:23

Requirements

Basic understanding of software development
Basic understanding of Testing | Quality Assurance
Willingness to learn and improve
In some areas GPT plus is used.

Description

This introductory course is designed specifically for Software Quality Engineers interested in leveraging the power of Generative AI to enhance their testing, automation, and productivity.

Throughout the course, participants will learn how to apply Generative AI techniques to automate the generation of test cases, simulate user behavior, create user stories, and generate test data. The course will provide a practical understanding of how AI can be used to improve software quality and boost productivity, rather than focusing on the underlying AI algorithms and models.

Topics:

Understanding Generative AI: An overview of Generative AI and its applications in software testing and quality assurance.
Automated Test Generation: Learn how to use Generative AI to automatically generate a variety of test cases, reducing manual effort and increasing test coverage.
Automated User Story Creation: Understand how Generative AI can be used to generate user stories, helping to streamline the requirements gathering and software development process.
Test Data Creation: Learn how Generative AI can be used to generate test data, ensuring comprehensive and effective testing while saving time and effort.
Code Investigation: Discover how Generative AI can assist in investigating complex code, identifying potential issues, and understanding code dependencies.
Code Explanation: Learn how Generative AI can be used to explain code behavior, making it easier to understand complex code and improve code quality.
Boosting Productivity: Understand how these Generative AI techniques can be integrated into your existing workflows to boost productivity, improve software quality, and accelerate delivery times.
See how to create a Performance testing Framework with CI/CD on cloud with AI
Crate your own custom GPT and publish it in the GPT Store
Understand Machine Learning and basic AI Concepts
Connect to the OpenAI Backend with the help of the REST API.

Who this course is for:

Business Analysts
Quality engineers
Software Engineers
Scrum Masters
Engineering Managers
Software Testers

CHATGPT for Software Testing | Generative AI

What you'll learn

Explore related topics

Course content

Introduction5 lectures • 34min

Introduction to Generative AI12 lectures • 45min

Introduction to Chat GPT Features7 lectures • 30min

Connect to Chat GPT with an API6 lectures • 18min

Quality Engineering from the future - AI Powered5 lectures • 27min

Generate Documentation (Test Cases, Artifacts) with Generative AI6 lectures • 45min

Create a Playwright Automation Framework with GPT with Canvas12 lectures • 57min

Open AI Codex for Playwright Automation6 lectures • 39min

Generative AI for Test Data, Test Automation and Coding18 lectures • 1hr 2min

AI AGENT - Create your Own AI Agent with FlowiseAI7 lectures • 50min

Requirements

Description

Who this course is for: