GenAI for QA - Masterclass in Testing & Automation

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Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will dive deep into how GenAI is transforming Quality Assurance (QA) and automation in software testing. From understanding the fundamentals of AI in QA to advanced applications like building web automation frameworks with AI, you'll learn to integrate cutting-edge AI tools and techniques to improve your testing efficiency. The course is structured to start with the essentials of setting up AI assistants like ChatGPT, Claude, and Google Bard for various QA tasks. As you move forward, you'll learn about prompt engineering principles and apply them to functional testing, building automation frameworks, and API testing. Each module is designed to teach you practical skills, from generating test cases to debugging and automating repetitive tasks. This course is ideal for QA professionals, software developers, and anyone involved in testing and automation. Whether you’re looking to level up your skills or embrace the future of testing with AI, this course will provide you with all the tools you need. There are no strict prerequisites, though a basic understanding of software testing concepts would be helpful. This course is suitable for intermediate learners. By the end of the course, you will be able to set up and integrate AI tools for automating testing tasks, apply advanced prompt engineering techniques, build scalable web automation frameworks, and enhance your API testing processes using AI-powered solutions.

Syllabus

Introduction to GenAI in Software Testing

In this module, we will introduce you to the world of GenAI and its pivotal role in modern software testing. You will explore why QA needs AI now and how it can significantly improve the speed and accuracy of testing tasks. Additionally, we will outline the core skills and knowledge you’ll acquire in this course for integrating AI into your testing practices.

Setting Up AI Assistants

In this module, we will walk you through setting up and utilizing different AI assistants like ChatGPT, Claude, and Google Bard. These tools will help streamline your testing workflows, making tasks like test case generation, bug reporting, and documentation automation faster and more efficient.

Prompt Engineering Principles

In this module, we will explore the basics of prompt engineering and its importance in obtaining precise AI outputs for QA tasks. You will gain both fundamental and advanced skills in crafting prompts, optimizing AI’s responses for more accurate and efficient testing results.

Functional Testing With AI

In this module, we will focus on how to apply AI to functional testing, from automating test creation to generating detailed test cases for web and mobile applications. You’ll also learn how AI can aid in crafting a comprehensive test strategy and improving test coverage and reporting.

Building Web Automation Frameworks with AI

In this module, we will guide you through building robust web automation frameworks with AI. You will learn how to set up frameworks, identify UI elements, refactor code for maintainability, and create data-driven tests. AI will also help you in retrying failed tests and generating advanced reports.

API Automation With AI

In this module, we will introduce you to the Rest Assured framework for API testing and demonstrate how AI can streamline the setup and implementation of your API testing framework. You will also learn how AI can assist in debugging and generating insightful logs and reports for API tests.

Pair Programming With AI Tools

In this module, we will dive into AI-powered pair programming tools like GitHub Copilot. You’ll learn how to leverage these tools to automatically generate test classes, parameterize test data, and transform manual test cases into automated scripts. Additionally, we will explore AI-assisted debugging and auto-documentation techniques.

Private Offline AI Assistants

In this module, we will guide you through setting up and using a private LLM for offline use. You’ll learn how to configure AI tools to remain secure and fully independent of external servers, enabling you to maintain full control over your testing tasks and sensitive data.

AI-First Automation With TestRigor

In this module, we will introduce you to TestRigor, an AI-first testing tool that automates test creation and execution. You’ll learn how to set up TestRigor for web and API testing, leverage data-driven testing, and take advantage of its self-healing capabilities for low-maintenance, reliable automation.