
English | Size: 6.5 GB
Genre: eLearning
Master Generative AI for Testing: Python, Playwright, and Behave BDD Frameworks for Manual and Automation Testers
What you’ll learn
Use Generative AI tools like ChatGPT and OpenAI API to create, analyze, and refine test plans, cases, and BDD scenarios dynamically.
Master Python essentials: variables, functions, file handling, and libraries like Requests for effective automation testing.
Build AI-enhanced frameworks using Behave BDD for API and Playwright for UI testing, focusing on dynamic and efficient test creation.
Optimize automation tests with AI: refine BDD steps, generate test reports, automate cleanup, and integrate advanced features.
Configure Jenkins CI pipelines to execute automated UI and API tests, generate reports, and streamline test workflows seamlessly.
Ensure test data privacy: anonymize sensitive data, use environment variables, and follow ethical AI best practices with ChatGPT.
Gain hands-on experience with real-world projects: automate Contact Us, Login APIs, and Goal Tracker API using practical exercises.
Learn advanced testing techniques like custom test runners, targeted execution with tags, and detailed reporting using Allure.
Why Generative AI in Software Testing?
Generative AI is transforming the software testing landscape by enabling dynamic test case generation, optimizing test execution, and improving coverage. Tools like OpenAI’s API and GPT4All empower testers to:
- Reduce manual effort.
- Uncover edge cases faster.
- Enhance both manual and automated testing workflows.
Why Python, Behave BDD, and AI-Driven Tools?
Python: A versatile, beginner-friendly programming language widely used for automation.
Behave BDD: A Python-based Behavior-Driven Development tool that uses the same Gherkin syntax as Cucumber BDD, simplifying test case creation and ensuring scenarios are clear for all stakeholders.
AI Tools: Leverage OpenAI’s API (ChatGPT) and offline tools like GPT4All to dynamically create, optimize, and refine test scenarios, reducing manual effort and improving test coverage.
Together, these tools allow testers to:
- Automate UI and API tests with AI, Python, Behave BDD, and Playwright.
- Dynamically generate and refine test cases using AI tools like ChatGPT and OpenAI APIs.
- Integrate into Jenkins CI pipelines for scalability and continuous test execution.
Why This Course?
This course is practical, easy-to-follow, and designed for manual testers and automation testers looking to upgrade their skills. Whether you’re new to automation or experienced in testing, you’ll gain hands-on experience with AI-powered testing.
(Note: To fully implement AI features programmatically, an OpenAI API key is recommended. OpenAI provides free credits for new accounts, but existing users may need to add minimal funds (~$5). Watching specific lectures without practical implementation is also an option.)
The course includes Before and After code examples, attached to the relevant lecture resources, to help you understand concepts step-by-step and implement them seamlessly.
What Will You Learn?
Generative AI for Test Case Creation
- Use ChatGPT (free or paid version) to generate test plans and test cases outside of code.
- Use OpenAI APIs to dynamically generate test cases and suggest step definition code within the framework (API key and minimal credits required for hands-on implementation).
- Explore tools like GPT4All for offline AI-powered testing.
- Quickly create optimized, AI-powered test scenarios.
Mastering Python Fundamentals for Testing
- Python basics: Variables, data structures, functions, and file handling.
- Work with JSON data and external libraries like Requests for API testing.
Building AI-Enhanced Automation Frameworks
- Behavior-Driven Development (BDD): Simplify test requirements using Gherkin and Behave.
- Automate UI Testing with Playwright and Behave (BDD).
- Automate API Testing using Python and Behave (BDD).
Advanced Features for Automation
- Use Generative AI to refine BDD scenarios and step definitions.
- Leverage OpenAI API to analyze step definition files and recommend optimized code solutions.
- Implement tags, custom runners, and generate detailed test reports with Allure.
- CI/CD Integration: Learn how to run tests continuously using Jenkins CI pipelines.
Data Privacy and Security in AI Testing
- Protect sensitive data when using AI tools like OpenAI APIs.
- Follow best practices for anonymizing data and managing credentials securely.
Additional Features
- Real-World Projects: Automate tests for a Contact Us Page, Login Page, and a Goal Tracker API.
- Practical Exercises: Step-by-step recordings with before-and-after downloadable code examples.
- AI-Powered Optimizations: Generate, analyze, and refine test scripts dynamically.
- Reporting: Generate detailed reports and attach screenshots for better test visibility.
Ready to Master AI-Driven Software Testing?
By the end of this course, you’ll have the skills to:
- Integrate Generative AI into manual and automated testing workflows.
- Build scalable and dynamic automation frameworks using Python, Behave BDD, Playwright, and Jenkins CI.
- Leverage AI tools to optimize and streamline testing processes effectively.
Let’s revolutionize software testing with Generative AI together!
Who this course is for:
- Manual Testers looking to streamline test case creation and enhance their skills using AI tools like ChatGPT and OpenAI API.
- Automation Testers wanting to build AI-enhanced frameworks for UI (Playwright) and API (Behave + Requests) testing with Python.
- QA Professionals aiming to integrate generative AI into their workflows for faster test case generation and smarter test execution.
- Beginners transitioning into automation testing with Python, Behave BDD, and Jenkins, with step-by-step, real-world examples.
- SDETs and Automation Engineers seeking to optimize and scale test automation using AI-powered tools, Jenkins CI, and dynamic reporting.
- Tech Enthusiasts eager to learn how to leverage AI tools like ChatGPT and GPT4All to create, analyze, and automate test scenarios.
- QA Managers and Leads interested in adopting AI-driven testing practices to improve productivity, test coverage, and efficiency.

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